Reading with the Stars…and Scholarly Peers

There are fewer tools that actually build an archive of live interpretation—as opposed to facts layered and ready for interpretation–around a stable text.“  – Augusta Rohrbach and David Tagnani

That’s where an amalgamation of Highbrow and Voyeur would come in.  The argument against the incorporation of humanities in English literature courses is solid, mainly, that it distances the reader from the text and removes the qualitative perspective only possible through human interpretation.  To replace it are mathematical calculations such as those presented in digital tools like Voyeur.  The creator of Highbrow, Reinhard Engles, describes his developing program as an “experimental genome browser for literary texts.”  Now, friends, genomes are inheritable traits of an organism.  Disbelieving as I was, I turned to the video screen casts and the electronic organism known as Highbrow.

Engles has put forth a set of 5 different tutorial videos, within each are demonstrations of the texts that have been uploaded into the program for use.  As Highbrow is still in its developmental stages, there are yet only 4 literary texts and 1 video to choose from:

Dante’s Divine Comedies

Ralph Waldo Emerson (Multiple Works)

Shakespeare’s First Folio (no references yet)

The Bible (King James Version)

——

Here are the strength and weaknesses, problems I found while working with Highbrow, as well as a basic “how-to.”  To start with I will mention that I will not be working with the Shakespeare set as it is incomplete and does not show, to the full extent, the capabilities of Highbrow.

“An Interactive Deep Zoom Widget:”

Rohrbach and Tagnani admit in their post “Reading with the Stars: Teaching with the HIGHBROW Annotation Browser,” that although there are plenty of tools available to ‘aggregate and organize existing information for users to interpret,’ these tools more or less become a step between students and the text and distance them from the literature itself.  Students begin to analyze the calculations formed by tools rather than “build an archive of live interpretation” from the text itself.  From this predicament and the partnering of Associate Professor, Augusta Rohrbach; PhD student, David Tagnani and Engles himself: ‘Reading with the Stars’ was born.  In their Washington State University classroom environment, Highbrow became a way for students to build upon both their own thoughts and conceptions about a studied work as well as the ideas and commentary of their peers.  ‘Reading with the Stars’ allows for a class to break beyond the barriers of a physical classroom and allow a ‘relaxed academic’ (oxymoronic in the eyes of many scholars, no doubt) atmosphere housed in a vast digital realm.

 

Putting it Together:

Aside from providing a digital meeting ground under the pretext of a .. well, a text, Reading with the Stars/Highbrow also allows an exceedingly more organized method for students to collaboratively annotate, highlight and organize ourselves beside the literature.  On an average day a student carries around their own weight in books – the conditions of which are dangerously suggestive of a younger sibling having had at them with a box of stationary.

Only somewhat inconvenient for budgeting students, we cry out for an answer, and Highbrow provides:

Highbrow: a clean and tidy alternative – and more. Click here for Engles screencast on “Interactive Editing.”

The ability to add/subtract “tracks” and edit the names of groups (which, by default, are sorted in chronological order – for the OCD perfectionist in us all) provides a unique experience catering to each individual’s preference.  Highbrow has a clean-cut interface with relatively easy navigation.  Zoom in with the mouse wheel, tapping the arrow key, or simply clicking.  Zooming in on specific segments allows you to view segments from books, to cantos, to verses and line numbers (in the case of Dante’s Divine Comedies):

Once you have registered, you can add your own annotations right next to the elite.  There are over 288,000 “tracks” of commentary, broken apart by centuries by default. It is interesting to see what 7 centuries of annotation looks like alongside each other, which were more interested and which were less interested: 1600 (Clearly everyone was wrapped up in Hamlet.)

 

Shortcomings:

Now come the annotations! At first, I had attempted to deselect all commentators aside from the track labelled “English” (seemed like a safe bet) and although it did produce English annotations, this greatly decreased the amount of notes in the right hand column.

My focus aimed at Canto V of Inferno (one of my favourite cantos from my favourite comedy) I decided to play with the “search text” button. As previously mentioned, Engles has designed a very clean interface and so it is quite simply point and click on the blue link in the upper left corner and a window will appear like the one pictured below:

What shall we look for in Canto V?  “Love” of course, although when searching, I would point out that your searches are limited to text only (or so I was unable to disprove) and not to the commentary.  Once you have typed in whatever desired lines or key word(s) preferred, simply click “search.”  Whatever keyword was searched will create a new “track” next to whichever others you had previously selected to the right.

Imagine my surprise when my search for “love” in the second circle of “The Lustful” produced 0 results. 

Then it hit me.  Oh yes, that’s right, it’s Italian.

Unfortunately, my Italian isn’t that strong otherwise I would have added in my own commentary next to  Alighieri’s own blood – Pietro!  I would imagine that in the near future Engles will be hosting further collaborations with other teachers, classrooms and of course, doing his own weekly adjustments to his program.  That being said, I was disappointed that I could not work further with Dante as I absolutely adore the Divine Comedies.  I would expect more works of Shakespeare will be added at the very least, along with more literature and perhaps a translated version of the Comedies – as the original is difficult to navigate even with a translator.

As this was the only real let down of the program for me, any other “weaknesses” I could possibly comment on an intelligent browser such as this – still so young in development, are few:

  1.  I had noticed that while searching through the text and annotations, I had only the option of scrolling with my mouse/track pad.  This became awkward and occasionally inconvenient when wanting to scroll with speed and precision.  This however, turned out to be strength on the programmer’s behalf as I later found out he added a side-scroll bar into the Emerson text.
  2. Also, searching with the “search text” tool does not search through the annotations: the most unique and intriguing part about Highbrow.

 

“Immersing into Emerson”

Although I am admittedly, and quite ashamed, not familiar with much of Emerson’s work, I had a lot more fun experimenting with Highbrow at this point.  I also had a lot more opportunity to see exactly why Rohrbach and Tagnani were suggesting that fun in a classroom could be facilitated with Highbrow.  So too, could I juxtapose the use of  Voyeur with it, discovering that the tool pairing make up for many shortcomings of the other and complement one another nicely.

I did not figure out a way of imputing the annotations themselves into Voyeur;  the results of which would have been more than thrilling for me at this point.  However, alternatively, I input the entirety of Emerson’s  “Intellect” into Voyeur and produced the following the results:

It was interesting to see (note: the top right corner of the ‘Word Trends’ chart) the correlation of Voyeur’s trending of truth and the identical spike pattern formed when put into a “track” in Highbrow.  True, data is data, the solidification of cohesiveness between the tools was refreshing given the complications presented throughout Phase II.  A few tools disagreed with one another more than once leaving room for doubt about the effectiveness of one or each tool.  I returned to the Voyant interface and I noticed shortcomings about Voyeur I hadn’t picked up on before.  When coming back to Voyeur again after a long absence and recently experimenting with Highbrow, I found that the Corpus Reader is excruciatingly ineffective in comparison to that of Highbrow’s navigation and heat-map highlighting layout.  Side by side, Voyeur is obviously lacking however, that is just the Corpus Reader.  Voyeur obviously has visual advantages, as best exemplified in my blog post: Singing with the Gravedigger, over Highbrow many of which are not as effective as they could be with Highbrow without first extracting user commentary.  I would love to see how Highbrow could be further taken into the other tools of ENGL203 and how it could match up with the other tools.  The ability to calculate frequencies within the text to then correlate with Highbrow’s human annotations based on activity spikes.

 

Putting it into Practice: “Reading with the Stars…and Scholarly Peers”

Rohrbach and Tagnani mentioned that what gauged the most reaction from students was an amalgamation of peer interaction and the public stage of the web.  This excitement and student exchange was part of the framework of our own classroom setting in English 203.  At one point in the “Prof. Hacker” blog post, they mention – “Indeed, when our students at WSU found out that they could read comments from a group of students approaching the text from a different context, the excitement was palpable: they wanted to see what students from another school and another kind of class thought about the text.”  Attempting to set Highbrow onto a classroom was probably one of the cleverest things possible for its capabilities and emphasizes each of the strengths that I discovered in my journey with “Reading with the Stars.”  They are as follows:

  • As the writers of the aforementioned blog post eloquently put it, Highbrow is like “reading through the lens of established experts.”   How much more fortunate can any student get?  For academic writing, the ability to have elite annotations from several centuries, alongside hypothesis testing tools such as Voyeur, would improve the quality standard of essays, academic papers and critical thinking as a whole.
  • On top of that, and providing further fuel for student minds, Engles is an actively involved programmer.  Rohrbach and Tagnani proved this in their described discourse with the creator,  illustrating him as delighted to assist and collaborate with them in their effort to establish “Reading with the Stars” at Washington State University.  Engles’ Alpha 2 is a screen cast about the highly enticing concept (and his plan) to incorporate multimedia into Highbrow.  In short, and certainly not doing the theory justice; the video really is a must watch, he is attempting to add the interactivity of annotating into multimedia such as videos as well as adding famous artwork based on literature as new tracks or perhaps timelines.  The video demo is, of course, not without his signature organization strategy of cutting the whole into tidy segments.  Further adding to his dedication, and as a result adding to the strength of the browser itself, Engles mentions that he is devoted to “adding new features every week for the next few months.”
  • We’re not done yet folks!  Highbrow/Reading with the Stars also provides potential benefits for the educators!  Associate Professor Augusta Rohrbach says herself that in her own classroom: “There is simply not time for everyone to contribute every class period, and the less confident and more introverted students find it easy to just hide in the crowd.”  This becomes true for every class discussing a literary work(s) and especially when it comes to analyzing said literary text; tenfold in a humanities lab.  When everyone wants to speak and provide a lengthy explanation, only 5-10 out of 100 get to speak and the hesitant/shy students are left quiet in the back row with their potentially break-through ideas remaining unfulfilled or expanded.  With Highbrow and Voyeur, alongside perhaps a more textual based tool like Wordhoard or Tapor; students can collaborate and build a strong and thorough breakdown of a text using mediums that best suits how their thoughts progress.  As commentary builds on the ever-growing student tree of side notes – the more each thought fuels newer, deeper questions.  Where the previous problem was too many voices and not enough space, the issue evolves into a strength for the classrooms digital environment: the more the merrier.  With so many voices and thoughts flowing via annotations, and with the superior organization of text Highbrow offers, professors can keep “track” of it (pun intended) easily by monitoring separate student tracks and annotation spikes.  More information regarding this and other ideas can be found in Engles’ third installment of his screen cast tutorials: Alpha 3: Interactive Editing.
  • One of the comment reviews about Highbrow I agree with the highest enthusiasm is that of anonymous ‘Tim’ who says “[It] would be wonderful for Buddhist studies which has 2000 years’ worth of commentaries.” This is particularly exciting for collaborating with Voyeur as the view of ancient texts through the lens of modern digital tools would breathe fresh life and doubtless new perspectives for new and old generations alike.
  • Lastly, I would like to point out a particular strength that Highbrow had a high hand over all of the tools English 203 studied: text location and isolation.  The precision Highbrow has displayed remains unmatched by Voyeur and to the best of my knowledge, any of the other tools.  Highbrow, with greater ease than it would be to flip to a chapter in a print book, isolates precise segments (such as cantos and acts) from the rest of the text – ready for examination by eager students.

Highbrow combines both qualitative and quantitative information, whereas Voyeur expands on the quantitative.  As I mentioned in an earlier “Phase I” blog post Voyeur is mainly a hypothesis testing tool – putting words into math-like calculations which may then potentially be further speculated.  Highbrow/Reading with the Stars, as it is peer and comment based, is most likely most useful for hypothesis generating.  Together: THEY WILL BE VICTORIOUS (too much?)

 

The End?
I think the connected functionality of this program will lead to a more united classroom.  It could potentially further encourage layering peer thoughts creating one or two linear thoughts as opposed to a separated classroom movement. Although English 203 came together, and watching it come together was probably one of the most enjoyable aspects about blogging, I could see a place for Highbrow as an addition to any classroom rather than a replacement altogether. Blog posts would continue to allow students to freely express and layout their personal thoughts on a page, easily a necessity in this course; and Highbrow to draw out the introverts and build confidence in their ideas as well as shine a new light on the same text for everyone to realize ideas they didn’t know they had.  The next logical step for books is digital humanities, evidently, but we don’t want to lose our relationship with the stories, authors and text. Together, we make it stronger instead of simply replicating the effect of annotations by peer commenting and annotating.

With the addition of Voyeur, visual stimuli would undoubtedly lead “students to think more deeply about those passages, passages that they may have initially ‘took at surface level,’” (as one student had mentioned) – not unlike the realizations of our own humanities course by semester’s end.  Although Highbrow does not at first seem much different than our own classroom blogging method, the ability to annotate alongside the text increases the student relationship with the writer and text (much like writing all over our hard copies has done for us in the past) and decrease writer’s block intimidation and perfectionism.  It’s like building an anthology, complete with graphs, for future classes or perhaps assisting other classrooms and students across the world!

 

It Begins at the Beginning and Ends at the End

Introduction:

I have stated many times how conflicted I have been about this class. Having absolutely no idea about what it contained when I first entered, I was first struck by two things. One, was Professor Ullyot’s absolute enthusiasm for the subject that he was teaching and the second was the how foreign the subject matter was to me (in the sense of the digital humanities). Having been raised in the first digital era and still retaining vague memories of dial-up, I was fully aware of the capabilities of computers, how far they have advanced and how they could shape lives and ideas. It was an oversight on my part that I did not fully recognize that they could also be used in analyzing English and the literature within it. Looking back I can now fully recognize my error however, my whole experience has come away a bit bittersweet. My personal tool which I used (Voyeur) was easy to operate however I felt that while it had a great number of tools, the number of useful tools that I possessed was somewhat low. However, at least my tool was able to operate on a fairly regular basis. Looking at the other word tools and that issues that they caused my peers, their irregularity has to be acknowledged as an issue that the digital humanities community must face if they wish their field to progress. However at the same time I find myself thinking of different texts that we would be able to analyze with these tools, despite their faults. That would be the enthusiasm of Professor Ullyot shining through.  This picture by Beetroot Design Group shows every “Romeo” and “Juliet” through the entire play connected by red lines with 55,4440 lines used total…

 

 

 

 

 

 

 

 

These pictures reminded me of the digital humanities and their ability to connect thoughts and ideas through a text that we may not have known about before. I love that about the digital humanities, however the flawed method that they are administered through causes me headaches and heartache.

 

Hamlet:

Having read Hamlet once before in high school, I felt that I had a fairly good overview of the play. While I think it would have been interesting to have different groups examine different texts within the separate tools, I feel that the use of a well-known text such as Hamlet allowed a good backdrop for learning the different nuances of the digital humanities. Since it is such a universally known story, it allowed each of us to concentrate on how the digital humanities tools helped us to understand the text rather then having simultaneously learn the plot and analyze the text. In my earlier blog post “Frustration and An Abundance of Claudius” (http://engl203.ucalgaryblogs.ca/2012/03/frustration-and-an-abundance-of-claudius/), I examined Claudius and his speech throughout Act 4 using Voyeur.  It was through the use of my tool, that I was able to identify Claudius’ concern for all of the other characters within the scene, repeatedly mentioning each one in turn. While this is a plot tidbit that I probably would have been able to uncover through a more through reading of the play, the digital tool allowed me to examine his speech in a different context using the Word Trends tool. Using that tool allowed me to examine Claudius’ behavior within Act 4 using not only the provided literature, but also the literature in a graphical form. As the digital humanities evolves and changes, so too will our methods of interpreting text and thus more nuances within the stories can be uncovered.

Voyeur:

While still in Phase I, my Voyeur group and I sat down and decided to discover our tool together rather than going off by ourselves and discovering it on our own. For our own particular group, this method worked very well. Being able to collaborate and use each other as resources became an invaluable aspect of the Phase II aspect of this course. In my Phase I blog post “Art Deco and Flexibility” (http://engl203.ucalgaryblogs.ca/2012/03/art-deco-and-flexibility/) I went over some of the additional tools that Voyeur had to offer and found them to be slightly lacking. Sure they looked pretty, however the way that they presented their information was vague and difficult to decipher. The balance between the aesthetics and functionality has to be maintained. While thinking of the future development of the digital humanities this aspect must be taken into consideration when designing future programs. One aspect of Voyeur which we found to be advantageous was the tools ability to analyze certain parts of text rather than being forced to analyze the entire corpus/text. It allowed for flexibility within the corpus while maintaining the same level of analysis as the larger bodies of text. While I do enjoy Voyeur for the certain advantages that it holds, it must be maintained that all of the digital tools must operate together in order to create a comprehensive picture of the text.

Tangent or Future?:

Are the digital humanities the future, or simply a tangent? I happily sit on the fence on this argument. While it is lovely to maintain that there are only two sides to this argument and pack everything up in little boxes and force people to each choose sides, the issue is more complex then that. On the one hand, technology is progressing at an extraordinary rate and advancing so quickly that I dare not even fathom what they might be capable of in the future. The insights that we gained from our tools while examining Hamlet were some that could have possibly taken years to undertake by hand. Voyeur adds a level of visual detail which helps some people to better grasp Shakespeare while some of the large corpus tools such as MONK analyze entire bodies of work and find the details within seconds. These are advantages of the digital humanities which cannot be ignored. However, does the rise of these new text analysis tools mean the failure of books and the abandonment of older methods?

Not necessarily.

While the new digital tools offer some new methods with which to analyze, the same job could in fact be accomplished by a scholar sitting at desk with nothing but pen and paper, it would take much longer for sure however in the end, the same result is gained. One also has to consider how long it takes to create programs such as these and how someone would have to go through every single manuscript word by word and mark down the speakers, the nouns, the verbs etc. Would that same amount of time also be used to gain the same results as sticking them into a computer to analyze? I must admit some weariness amount the foothold that technology has gained on our lives. In academia the effect is omnipresent, in the ten courses that I attended in the last year of university only one did not require a computer. Professors post their notes on Blackboard or use texting polls in class or use digital textbooks and quizzes to test our knowledge. In examining this I have to wonder what would occur should one part of it fail? No digital systems is without it’s flaws as evidenced by to error messages ourselves faced when completing this project.

My main point is that my book won’t break when I hit it with a hammer and it never runs out of batteries.

Conclusion:

While this class has had it’s share of ups and downs I am very glad that I experienced it. It opened up my mind to new methods of analyzing text and introduced me to new facets of one of my favourite Shakespeare plays. The digital tools must be used together in order to have the most comprehensive picture of the text you are attempting to analyze. In the manner of future Vs. tangent, I back away slowly and embrace a more ambitious future where they both exist in somewhat strained peace.

Final Post

Ready, Set, GO

As a traditional reader, one is able to certainty pick up on thematic clusters, interactions, structure and so on, but it isn’t until you start using digital tools, where you are absolutely able to see both qualitative and quantitative occurrences, such as repetition of words and or various references to God for example. Digital tools take the best of both worlds, and slot them together.  So to summarize my argument, I strongly conclude that digital tools are the future, providing aspects of traditional readings whether it be through creating a hypothesis or by gaining qualitative and or quantitative information. However, the combination between digital tools and traditional reading is the most complete way to analyze a text.

The Beginning

Thinking back to the beginning of the semester in January seems like it was forever ago, but it was the beginning of my digital humanities journey. Coming from the lands of computers, blogging, and the creation of internet pages, I could not have ever imagined all the possibilities such tools could offer to enhance my understanding of Hamlet. My initial thoughts were “Professor Ullyot, how could you combine Shakespeare, who literally has a language of his own, with digital tools?”  Was this possibly the most awkward/ complicated combination ever? No it wasn’t, if anything it was a genius move. One thing I learned about reading Hamlet in two different semesters, as I mentioned in my other blog was that reading Hamlet isn’t as straight forward as picking up Harry Potter, and connecting the dots as the story unravels.  Hamlet is a text that one must actively read, while physically connecting the dots via notes in the margins. I did do this in the fall semester; however, I did not dive into the text and ask questions that were deeper than the surface. Or in other words, my interest didn’t lie in creating a hypothesis and making conclusions with solid evidence. While reading traditionally, repetition occurred, God references were used, and various tones were apparent throughout the text, but my questions were: “who cares and why does this matter?”. Through the use of digital tools, I learned that in fact these questions, references, and instances of repetition Shakespeare uses, are important to the text. If anything, they are the most interesting aspects of the text.

For example, although these are not the most interesting results, this tool from TAPoR pulls out names (or capital letters to be more correct) like Mars, Mercury and God. The way that this tool is capable of doing this, may for some reiterate important ideas or references, perhaps like Christianity for example.

Traditional Reading Benefits

  1. You can always trust the book as a correct source
  2. Structure is easily identified i.e.) line, sentence structure, interruptions
  3. Thematic clusters can be determined i.e.) body parts: head, heart
  4. Interactions can be determined i.e.) statements, questions, and answers
  5. Tone and performance is evident i.e.) is a character giving advice? Or is he angry?
  6. Figures of speech: metaphors, similes, double meanings

 

Flaws of the Tools

In order to use digital tools, you need to be smarter than the computer. Yes, the computer is a fast worker, but its brains do not equal the power of its user. Therefore, you must know what you are looking for, and at times you may need to question your results.  During phase 2, it was not until I compared my findings with other results from different tools (Monk, WordHoard, TAPoR, and WordSeer), that I really learned the downfalls to Voyeur. Quite often, Voyeur could not find words that certainly did appear in the text and in other tools.  The most frustrating example I had of this was found when searching for the word tongue in phase two in act 3. Voyeur told me 0 results, BUT I physically saw the word tongue with my own eyes in the text, and other tools were showing results of these occurrences. Here are three occurrences within act 3, where voyeur apparently was not recognizing any of them. Cool.

 

The work of Monk

More downfalls…

  1. Error messages are common
  2. Different versions of the text(s) can change your results
  3. Shakespeare’s language versus modern language = problem
  4. Tools search exactly what you type

 

Discovery

Warwick writes “the digital medium allows for a more inclusive approach to academic research, whereby users …become part of the process of discovery and interpretation”. Warwick’s words are exactly right, when your chosen tool is willing to work with its user and provide its user with correct results. Digital tools do not give you answers without work, it gives you data. Digital tools, Voyeur in particular, works as a hypothesis generator as a beginning step towards success. This is the beginning of your process of discovery. Right away by just looking at the visual word cloud you are able to see the words that occur most often: HMLT, Lord, love, play, and make. Or if you are a person who is more number orientated like I am, you could use the frequency chart, where numbers are listed by the most frequent used words.

While looking at the frequency chart for act 3, I’ve been given quantitative evidence: love is a word that occurs most (23 times) in act 3.  Although this is an evident theme a traditional reader could have easily pulled out after reading Hamlet, we must remember that we are only in the stage of constructing a hypothesis, where Warwick writes “users of digital resources do know what they need and if they don’t find it they will not use things that are unfit for their needs”.  In other words, digital users will keep looking until they are able to collect the evidence, whether it is qualitative or quantitative data, to make a conclusion. By keep looking, I mean these tools are not capable of pulling out the differences between how the word love is used. Hamlet states, “I did love you once” (3.1. 114) when speaking to Ophelia as way to express an emotion that was once there. In the play put on by the Players, you read “you shall see anon how the murderer gets the love of Gonzago’s wife” (3.2.256). Yes, love is mentioned, but it is not really used in the context of an individual expressing love as an emotion to another individual.  Depending on what a user of digital tools was looking for, the quantitative data could distract you from coming to a correct assumption about love in the play. There are many other occurrences where this issue was present.  Hamlet/ Shakespeare uses the words honest and fair to question Ophelia, when in modern day, these terms are used very differently.  See my blog post for a further explanation and dictionary definitions.

Traditional Questions

With traditional reading though, what would one do with the theme love? We could use qualitative evidence to compare the different types of love? Or analyze how Hamlet uses the word love? Is he really in love with Ophelia? Regardless of the direction one may choose, I feel like a conclusion can be reached, but the so what factor is missing. Why not take your hypothesis to the next level and use frequencies, visuals and chart comparisons to deepen your analysis?

Making Progress

Since we were using digital tools, I decided that it wouldn’t make sense to go to the text we used in class to look for information, and then put it into my program. I tried to stay dedicated to digital tools. Luckily, my tool Voyeur allowed for me to maintain my dedication. Voyeur provides a corpus reader, which is practically the text itself. For some tools, this is where there was some disconnect.  Most other tool users could not a) read an entire act, scene, or play b) modify their text and or c) take their data, and achieve visual results. I believe most students will agree that tools are great for quantitative data, but Voyeur is much different. It combines the best of both worlds like mentioned above. (To be honest, the second half of the semester my text book of Hamlet sat collecting dust). Voyeur was, however, beneficial in the way that I could modify Hamlet to either include, or exclude things that were tainting my data. For example, one of the biggest downfalls to Voyeur was the fact that speakers could not be separated from their names being mentioned. In other words, this was ruining my quantitative data, by making it seem like Hamlet was mentioned 100 times, when over 75% of the Hamlet occurrences was when he was speaking.  TAPoR, however, was the tool which was responsible for gathering when characters spoke.  By separating character’s lines via TAPoR, then putting my information into Voyeur, it was much easier to analyze each character’s word choices, emotions (qualitative) and frequencies (quantitative) and or information.

Voyeur- Results are tainted because the file has not been edited

 

Because Voyeur offered the ability to read the text through the corpus reader, I was able to gain both qualitative and quantitative occurrences, which I don’t think was something I could have necessarily gained through traditional reading on its own.  Although I wasn’t able to “make notes on a piece of paper, doodle, fold it up and carry” Voyeur with me, like Warwick states when she compares traditional texts with digital humanities, the information I was able to drag out of Voyeur was something beyond any traditional reader could gain alone.

Corpus Reader - Just like a book ...

 

The conclusions I came to, as seen in my blog, was a combination of reading through the corpus gaining qualitative and quantitative information, then submitting it into the program to further analyze the qualitative data. Even though I was randomly typing in words, checking their frequencies and looking for connections, this would have been completely impossible through traditional reading. Again, I know this because the first time around reading Hamlet, these themes were overlooked, probably due to the complexity the story line or language.  First I noticed that Shakespeare makes references to body parts, for example “go, go, you question with a wicked tongue” (3.4.10), or compares words to daggers, “I will speak daggers to her but use none” (3.2.386).  By slowly typing in each word in search bar that was a part of the body, my phase two group was able to make the theme of our presentation based on senses (eyes, hearing, and speaking/ tongue). Finding this information was new to me. I never would have been able to make the connection between all of the senses, if I did not break down act three, and draw connections through the frequency occurrences.  I think by slotting information into a program allows you to slow down and analyze it in a way you never would. Like mentioned above, without the use of numbers or data to prove your point, the so what factor occurs. I strongly believe that with the help of digital tools, you are able to fill the so what void. It is like science. You make a hypothesis, but until you prove your hypothesis with data and results, it is invalid and useless.

Traditional vs. Digital

I believe that a reader could easily create a hypothesis, compare themes, words and references without the use of digital tools.  However, I strongly believe that with the help of digital tools, their speed, frequency lists, and visuals, can provide that extra bit of information that can take understanding and learning to entire new level. A computer or a digital tool, as we know, is smart, but not as smart as its user. Tools are full of flaws that can often taint our understanding if further investigation is not taken. In Warwick’s blog, she quotes Helen Chatergee who does work at UCL Museums and “suggests that when we handle real objects, different parts of our brains respond than when we see a digital surrogate”. It does not specify how the brain responds differently, but the fact that this quote states that it does, demonstrates that both digital tools and traditional reading used together could provide the most useful results. At least this way, our brains are responding differently to each method to gain a complete picture.

 

Works Cited

Shakespeare, William. Hamlet. Ed. Ann Thompson and Neil Taylor. London: Arden Shakespeare, 2006. Print.

Warwick, Claire  http://clairewarwick.blogspot.ca/2012/01/inaugural-lecture.html

 

The End of a Beginning

I am writing on something that before this class I never knew about let alone expected to ever find myself writing about.  I have taken a class this past semester that teaches about the digital humanities as a method for literary analysis, but my reasoning for taking that class should be made clear, it is a requirement for an English degree that I must have before I am allowed to go into the field of education.  Because of my degree requirements, I have found myself taking a literary analysis class that was much more than I ever expected it to be.  I am writing about my first experience with something that is new to me and also happens to be useful and enjoyable, that is, the digital humanities.  In this post, I will be analyzing the feasibility of an idea that involves mixing together both the digital approach to the humanities and the traditional approach to the humanities for the sake of education.

Mixed Motives and Mixed Results

I have many motives for writing this extensive blog post, the fact that it is a requirement for English 203 is not the least of those motives but this is the only mention which that particular motive will receive.  First among my motives listed here is the fact that I intend to go into the field of education upon completion of my university education, so I must ask myself, how would the digital humanities affect or be affected by education.  My second motive listed is the fact that I was influenced at one time by an English professor to believe that, remaining realistic, there is no definite right or wrong way to analyze a text and therefore there is no definite right or wrong analysis of a text; so believing this has also allowed me to have an open mind concerning the humanities.  Therefore, I felt that the subject must be mentioned.  My third and final motive listed here, is the fact that I just wanted to compare the traditional aspects of the humanities to the more modern aspects of the digital humanities.  All of these motives together are why I picked the blog post from the Digital Humanities Now website that I did.  That particular blog post is one written about interdisciplinarity and curricular incursion that can be seen if you go to the following link,

http://ryan.cordells.us/blog/2012/02/20/dh-interdisciplinarity-and-curricular-incursion/

My thoughts were that I wouldn’t find a better blog post to compare both aspects of the humanities as well as the effects that they have had on education and vice versa.

Pedagogy

I intend to go into the field of education, because of this I feel that it would be good to know some of the proper approaches to the Digital Humanities in case I ever end up teaching something about them or having to introduce a course on the digital humanities to a school board or committee.  The idea of interdisciplinary actions in the curricular aspect of the humanities is essentially, new revolutions in the humanities and how they affect or are affected by pedagogy and that is what I am interested in.  The digital humanities are a new and different method of teaching English that may be viewed more receptively by students than the traditional approach to the humanities because it can be easier for some people to acquire an analysis of a text through some of the tools available.  The Digital Humanities may also be more appealing to a number of students because of the more relaxed writing style that is available through them.

Right and Wrong

I have the personal belief that there is no definite right or wrong approach to textual analysis which extends to the idea that there is no definite right or wrong approach to the humanities.  That particular belief is supported by the idea that each and every person analyzes a text differently.  Therefore, there are as many perspectives of texts as there are people.  Each person gains a different perspective of a text just by reading it and the tools available through the digital humanities have the capability to verify, expand and build upon those various perspectives.  Finally, I feel that the line between right and wrong analyses of a text is really blurry, therefore, who am I to judge whether or not a new method of analysis is definitively right or wrong.

Comparison

I would like to compare what I have learned of the digital humanities to the information that is available to the world at large and to what I have learned about the traditional approach to the humanities.  Before starting the literary analysis course with Dr. Ullyot, I knew very little about the digital humanities, in fact, I went into the class thinking that it would be based on the classical literary analysis class where the students read the text, come up with a quantitative analysis of the text, write a paper on that analysis, and then when they are done with that, they proceed to rinse and repeat.  It is a good thing that my assumption was way off base, because a class that I expected to be dull was actually highly interesting as well as informative.  In the past, I have only ever approached the humanities in the classical manner and I have always been comfortable with the traditional method of textual analysis where a person reads the text and attempts to draw conclusions from it and prove those conclusions by writing an essay.  I was only a fan of this, however, because I am a relatively strong reader and it has always been easy for me to read a text and draw a decent quantitative analysis from it.  For me, the only problem with the traditional approach to the humanities lay in the aspect of having to write an essay, something that I am not very good at doing.  The Digital Humanities are really quite new to me; in fact, at the beginning of this past semester was the first time that I had ever heard of them, let alone studied them.  At first I was really skeptical of the idea of using technology to analyze texts as well as the idea of posting my findings on Twitter or a blog.  The reason for this was because of the fact that the only examples of either one that I had ever come across were pointless wastes of time with the people who wrote on them badly abusing the use of the English language.  After I realized that both Twitter and blogging could be extremely useful, I came to accept the idea of textual analysis using computers, to be honest, for me it was a journey of small steps.  I am still not entirely comfortable with the methods of textual analysis available through the digital humanities, but I will say that they are an amazing way to verify or prove my own quantitative analyses and make them qualitative.  I am also much more comfortable with the more relaxed writing style that is afforded to me through writing on blogs rather than a formal essay.  I feel that if the best of both aspects of the humanities could be mixed together, then there would be a truly excellent dynamo in place for the study of literature.

How it Was Done

Throughout the course of the semester, the people in English 203 learned about different tools available through the digital humanities and what those tools are capable of using a base text of Shakespeare’s Hamlet.  First we learned how to operate one of five different tools, and second, we got together in groups with four other people who all used different tools and worked together to analyze a portion of Hamlet.  This exercise taught me much about one tool, a little bit about the other four, and a great deal about how the digital humanities work.  The idea or concept of having four other people working in concert with me on the same project being able to converse with them via email or blog really made things easy.  I learned through the use of the blog posts that we are required to do, that the digital humanities are entirely collaborative.  Any one person with access to the blog was able to comment on or contribute to anything that I chose to write about.  Because of this, anything written on a blog in the digital humanities is constantly exposed to public scrutiny, as well as any new developments in technology, which are constantly occurring.  The concept of putting your findings in a blog post is a new and highly effective way to keep your writing and information perpetually up to date.

Phase I

            I was given the Voyeur or Voyant tool developed by Stefan Sinclair and Geoffrey Rockwell to learn how to operate in order to analyze the text of Shakespeare’s Hamlet in the first phase of our class programme. http://hermeneuti.ca/voyeur

By learning how to use it, I discovered that the Voyeur/Voyant tool is very easy to use, especially for someone like me who is not very technologically adept.  I also learned that Voyeur/Voyant has a very open user interface which makes it very easy to start out using, just input your text and go to town basically.


Between the Phases

I used the tool that I learned about earlier in order to study Hamlet and verify qualitatively my own quantitative analysis of the text.  As I mentioned before, I have very little trouble with reading a text and coming up with a quantitative analysis of it.  Therefore, I thought that it would be easier to use my tool in order to verify my own analyses and make them qualitative rather than use it to come up with entirely new analyses.  Because of this I used the Voyeur/Voyant tool as a hypothesis testing machine and achieved what I believe to be excellent results.  I am not saying that it is not a hypothesis or conclusion generating machine, because I believe that it can be used as such; what I am saying is it was more practical for me to use Voyeur/Voyant in the former capacity.

Phase II

Once I had a firm grasp of how to use Voyeur/Voyant, I was pooled into a group with four other people who had used different tools than my own in order to see how well our tools would interact; this was the second phase of the class programme.  Most of the members of my group agreed that their tools were extremely viable in the capacity of testing hypotheses.  In fact, we made a quantitative analysis of Act II of Hamlet regarding surveillance, and between the five of us and our tools we successfully proved our analysis.  Throughout the course of the second section of the class, I came to the conclusion that no matter how good my tool was on its own, it could always be boosted up or helped out by another tool’s unique functions.  In my case, the tool that helped my own out the most was the Wordhoard tool developed by Northwestern University, http://wordhoard.northwestern.edu/userman/index.html .  I found that Voyeur/Voyant wouldn’t actually count how many words a person said, only how often they spoke, where Wordhoard would do exactly what I needed in that respect.

The Rewards

            After taking Dr. Ullyot’s English 203 class as well as reading Ryan Cordell’s blog on interdisciplinarity I have come to the conclusion that there is a place in the humanities for technology, I am not saying that it will completely overtake the traditional approaches to the humanities, but that there is a place for it.  I feel that the opinion stated in Ryan Cordell’s blog that “for digital humanists to make a real incursion into the field of literary studies, we have to start presenting in non-DH panels” (http://ryan.cordells.us/blog/2012/02/20/dh-interdisciplinarity-and-curricular-incursion/).  Even though not all people agree on the concept of the digital humanities, and not all of them communicate in the same way, in the words of Ryan Cordell, “we have to start actively seeking out colleagues who don’t know what we do—perhaps even those who don’t like what we do. We have to talk with colleagues who don’t tweet” (http://ryan.cordells.us/blog/2012/02/20/dh-interdisciplinarity-and-curricular-incursion/).

My Experiences and Responses

I have been introduced to the digital humanities and learned about them through trial and error in Dr. Ullyot’s class.  Now that I have done that, I am far more comfortable with the digital humanities now than I was upon first hearing about them and I am far more receptive to the idea of using technology for the purpose of textual analysis.

Results

Throughout the course of the semester, I have learned how to operate the Voyeur/Voyant program in concert with four other members of the English 203 class.  I have studied Act II with four other people who have all learned how to use different tools available through the digital humanities.  We discovered that the different tools in the digital humanities work better together than they do on their own.  When my Phase II group and I agreed that our tools worked better for them to verify their own findings rather than discover new things, I came to the conclusion that like the different tools in the humanities, maybe the two aspects of the humanities would also be able to work together in order to be much more useful and adaptable.

My Own Conclusions

My conclusions on the whole are that I accept the digital humanities as a new and improved method of testing hypotheses even though I am more comfortable with the traditional version of the humanities.  From my experience in both the traditional humanities and the digital humanities, I have come to the conclusion that both aspects of the humanities would greatly benefit from interaction with each other.

Voyant Tools analyze Voyeur blog posts

Phase 3 of English 203 is partly about reflecting on the process from January to now, so I thought I would initiate them with a bit of meta-analysis.

I was wondering what Voyant Tools could reveal about the blog posts in English 203, so I pasted the URL for the Voyeur category into the “Add Texts” search box and clicked the “Reveal” button. Here’s what came out:

What it shows is that those 33 posts there are 18,380 words (or ‘tokens’) and 2,789 unique words (or ‘types’). After eliminating the stop words I found that the most common words were voyeur, hamlet, act, words, and tools.

Here’s a longer list, so you can see relative frequencies. What’s interesting here is that voyeur outnumbers voyant by 186 to 30. A lot of the words relate to the mechanics of the course: posted, group, phase, blog. Love and death — those eternal themes! — are present, and characters.

So I hope this brief post has piqued your curiosity about the kinds of results you can get when you use the same tools on the texts you’ve generated yourselves.

 

 

 

Meanings and Searches

So, I thought that I would be brilliant with this blog post and try to do something cool like look up the meaning of the word voyeur on the Oxford English Dictionary website.  In hindsight, it really wasn’t that smart, apparently voyeur doesn’t have a very flattering definition.

I knew about the existence of this less than flattering definition of voyeur before, but I really hoped that there would be a definition that was related more to viewing and less to sexual tendencies.  Seeing as there really isn’t one though, perhaps that is why the makers changed the name to Voyant, which when looked up on the Oxford English Dictionary website you get the following.

This is a name for this program that actually could have meaning, rather than making the user feel like a Peeping Tom.

Using the Voyeur/Voyant program, I have found that you really can see a lot of things about a piece of written material when utilising it, however, I find that the voyeur program is more capable of taking a qualitative analysis of a text and making it quantitative than it is capable of developing new ideas about the text.  Take for example the idea that love and madness could be related, that is a qualitative analysis of Act Two and actually one of the themes to that particular act of Hamlet.  Punching the words, Love and Mad into the word frequency tool on Voyeur, a researcher would see something like the picture below.

However, I have also discovered throughout Phase II that all of these programs do not work nearly as well on their own as they do in the company of others, particularly the WordHoard Program.  I can find out who says what, where they say it, what they say around it, and when they say it; but I cannot find out how much they say, for that I need to rely on a program like WordHoard and my counterpart in the Act Two group, Jennifer, to tell me things such as, if Polonius talks more about madness to Ophelia, the King, or Hamlet.

Singing With the Gravedigger

The song alluded to in Act 5, scene 1 is ‘I Lothe That I Did Loue.’  An excerpt from the song suggests it is a formal song, most likely sung by jesters in court.  The fact that it is sung informally by a commoner/gravedigger (“ah”, “oh”) serves as a parallel to how the rich and the poor become equal in the grave.  This particularly grave (pun intended) scene  emphasizes a key theme in Hamlet: the nature and physicality of mortality.  Hamlet’s soliloquy when speaking of his dear friend Yorick as well as his conversation with Horatio, plays well with the gravedigger’s song. The pairing in this particular scene draws out the meaning in what the other (between Hamlet and the song) is saying.  Evidence in the text suggests it is very likely that while Hamlet was performing both his soliloquy and speaking to Horatio, the gravedigger continued to sing his song in the background.  A performance available on youtube demonstrates how this may have been performed at The Globe; listen closely to the gravedigger in the background as he continues to sing.  This juxtaposition would cement to audiences, of varying backgrounds, the truth in Shakespeare’s tragedy by having it both sung informally atop Hamlet’s formal speech. So too, does this layering balance comedy and tragedy at once, further complicating the mystery surrounding whether Hamlet is a tragedy or a comedy.

Evidence supporting the theory that the gravedigger does in fact continue to sing is the undeniable fact that the song presented in act five of Hamlet is an excerpt from ‘I Lothe That I Did Loue.’ otherwise known as ‘I Loathe that I Did Love.’  That approached, there are obvious huge gaps in verses which, presumably, would have been sung while Hamlet was speaking.  Although the subject matter Hamlet elaborates upon does not mirror the absent verses (from the text) both the voided paragraphs as well as the highlighted paragraphs present enlightening characteristics towards the play’s whole.  For time’s sake, I too shall exclude the verses that were not present in Hamlet – however, their relevance should not be slighted.

Hamlet/Gravedigger’s version:
” In youth, when I did love, did love,
 Methought it was very sweet,
 To contract, O, the time, for, ah, my behove,
 O, methought, there was nothing meet.”
‘I Lothe That I Did Loue’ Original:
“I loathe that I did love,
In youth that I thought sweet;
As time requires for my behove,
Me thinks they are not meet.”

Quick View of Similarities:
love
thought sweet
time for my behove
methought/thinks not meet

Presented above are the first verses of the two songs discussed, back to back, giving way to many mysteries.  Evidently, there is a repetition of love as well as an informal jaunty-like verse used by the gravedigger: “o, the time, for ah, my behove.”  Both deviations from the original song are perhaps to properly fill the Shakespearean meter.  A further mystery of the changes present in Shakespeare’s edit of the song is a questionable changing of “me thinks” to “methought” to which I can give no proper reasoning for.  Another curious change: from “youth” to “loathe” to only later resubmit “youth” in the preceding line. What can be salvaged from this chain of mysteries, and especially from the concordances between the two different songs, is the combination of “youth,” “sweet” and “love.” In my view, these three words are presented in a fashion that dictate the incapability of sweet young love having any accordance with time – being that, young love is doomed to fail. This reflects almost certainly on Hamlet and his dearly departed Ophelia.

In the screenshot above, I have outlined the basic comparison of both the original and the Hamlet version of the song.  The first stop in examining the songs through Voyeur was to sort the word count from highest frequency to lowest.  This, squared off in green, reflected the above (underlined) key words in the corpus: i, did, love, behove, for… The highest frequencies interestingly begin to form a phrase of their own to describe the raw meaning of the submitted verses.  Surprisingly, “love” squared off in blue in Cirrus, ranks high in usage however, “i” typically has no place in songs about love. Not getting ahead of ourselves (“i” will be further examined later) “love” also plays as strong of a role as “youth” and “sweet” whereas “loathe” (squared off in a teeny-tiny little orange box) plays a barely significant role in the songs.   This fact alone is interesting given “loathe” is found in the title.  As a side note, it may be interesting to note that out of 52 words, 33 are unique in placement.  Simply decoded: over half of the words present in the songs submitted back-to-back into Voyeur, are inconsistent with one another.

Putting these findings aside, I pursued the use of “i” within and between the two songs…

I submitted the two songs separately into Links, a tool in Voyeur that provides a visual stimulus of the links between words within a literary corpus, and received almost identical results – an example shown above.  The results, identical to one another, were also similar to the earlier Cirrus and Word Count results: “i” is undoubtedly the focus.  These tools being simple and similar in function, I finally decided to brave… Mandala.


Yeah, it’s intimidating.

I hoped for the best when selecting the option to remove all magnets and “surprise me!”  There is no room for internet memes and vernacular (word of the day: that one’s for you Act 5 group,) however in this case my reaction was no less than an internet blog appropriate: “LOL.”  I proceeded to “remove all magnets” sans-surprise.  Lo-and-behold, Mandala became my favourite and potentially most useful tool (move over Word Frequency Chart) as I slowly developed what you see before you.  Allow me to explain:

The aim: “i” – squared off in orange and bubbled in pink.  I added “magnets” for each key term (the biggest bubbles mapped around the circle) and “i” attracted the most ‘mini-bubbles’ – staggeringly so.  The fact that it produced a total of 23 matches in both songs and 17 unique matches is not even the most impressive part.  All of the sectioned magnets with multiple colours are the matches “i” produced with the other key word magnets.  Translation: “i” found a match within the songs with every key word with the exception of “death” (I put in the full version of both songs for Mandala when the singular verses produced uninspiring results.)  After this find, I added the opposing magnets “you,” “thou” and “thee.”  “Thee” produced nothing, so I removed the magnet, while “thou” produced one match and “you” produced 7… not even half of the attractions “i” produced.  Both added to the total matches of “i.”  What this all potentially means is that the personal affect of “i” is a very intentional use of the song for Shakespeare in writing Hamlet, and especially in writing this scene.

I decided to dig deeper… Could this perhaps be a very personal scene or act for Hamlet and perhaps Shakespeare, the man? Can the overpowering use of “i” over “you” in the context of these two songs have a similar impact on act five and the entirety of the play?

Well now, isn’t that interesting…

Moving on.

There are a couple more verses also taken from ‘I Lothe That I Did Loue,’ as the gravedigger continues to sing:
“But age, with his stealing steps,
 Hath claw’d me in his clutch,
 And hath shipped me into the land,
 As if I had never been such.”
(HUGE gap in song)
“A pick-axe, and a spade, a spade, (symbol of cosmic tree: life and death)
 For and a shrouding sheet:
 O, a pit of clay for to be made
 For such a guest is meet.”
           [Throws up another skull.]
“O, a pit of clay for to be made
For such a guest is meet.”
*The full song for the original is available here for comparison.
Here too, is an example of repetition: “O, a pit of clay for to be made/For such a guest is meet.”  These lines, to me, reflect the opening verse “me thinks they are not meet.”  Coming full circle, at least within the scope of Hamlet, from ‘not meeting’ to “meet”.  What perhaps allows this and also gives reasoning to why Shakespeare may have cut off the original song at this point is the suggestion of passing time.  In the first line “but age, with his stealing steps” suggests that the youthfulness of the love first discussed has dissipated and age has overcome the initial problem of youth breaking sweet love.  Unfortunately, what seems to replace “youth” as love’s antagonist is it’s cure: age.  What appears to be implied is age grabbing the lovers and sending them to their grave (“a pit of clay for to be made/For such a guest is meet.”)  The emphasis on the last pair of lines in the gravedigger’s song is undoubtedly a foreshadowing of Ophelia’s funeral and the irony of Hamlet’s ignorance of his lover’s death as he laments over “poor Yorick.”  The evidence of the song’s relevance to the play’s whole is provided in the screenshots below.  Using Voyeur I separated the play into 5 segments and submitted both youth and age into the word trends chart.  Clearly visible is the sharp incline of the usage of “age” nearing the play’s end and the sharp decline of the use of “youth.”  As reader’s of Hamlet all know, the love between Ophelia and Hamlet is exaggerated nearer to the beginning of the play, and death envelopes the end.

As a final thought towards these verses and their singer, the inserted stage direction to throw up another skull perhaps alludes to the circle of death.  The gravedigger had earlier mentioned in his riddle that he builds the most permanent houses as his are for the dead and last until judgement day.  However, while he sings he is clearly unearthing bodies to make way for new ones: rendering his houses impermanent.  For Hamlet’s part, he too circulates dead bodies but within his heart.  As he laments the death of beloved uncovered Yorick, he soon will be grieving heavily over the death of the body of Ophelia – soon to be replacing Yorick in the same grave.  All of these events, irony intact, insulate Hamlet’s soliloquy in act five.

Frustration and An Abundance of Claudius

Well we have reached the end. It feels strange to think that this is the last blog post. It feels like only yesterday when we were starting out in this course and already we are nearly finished it. Can you believe that I had never even heard of the digital humanities before January? Okay, musing over.

Let us jump into the project.

Looking past the ‘code names’ here, are the most frequently used words within Act 3 Scene 4 (which has approximately 1,789 words taking into account the ‘code names’):

We can see in this scene that Hamlet wants his mother to see what Claudius truly is as emphasized by the frequency of the words of ‘eyes’ ‘sense’, ‘look’, ‘come’ and ‘mother’. Now Kira, (the wonderful TaPOR member of my group) and I have been collaborating on examining the words of specific characters speeches throughout Act 4. Using the ‘Extract Text’ Tool in TaPOR she has been able to isolate several characters speeches throughout the Act including Claudius, Hamlet, Gertrude, Laertes and Ophelia. Now Claudius speaks the most in this Act by far, speaking just over 2,000 words total with Hamlet coming in second with 716 words and Gertrude speaking the least speaking time of all of the main characters, coming in at a mere 332 words. Now if I take all of Claudius’ words in the Act and stick them into Voyeur this is the result that comes out…

Claudius is very concerned about every other character in this scene. The fact that he is concerned about Hamlet is made obvious by the scene where Claudius is interrogating Hamlet over where he hid Polonius’ body and he both comforts Gertrude after her encounter with Hamlet and successfully talks Laertes down from the rage he felt by the fact that his Father had not been given a proper burial. In fact Claudius appears in every single scene in this Act minus the scene where Hamlet meets up with Fortinbras’ army. In first reading this Act my first impressions were of Hamlet’s wit when asked what he done with Polonius’ body (“At supper”) or of Ophelia’s descent into madness and her subsequent death. I had never before realized just how much Claudius appears in this Act until examining it with my digital tool.

Speaking of digital tool. Guess what I got today…

My first digital bug! Yeah! That sign kept showing up for ten minutes while I was trying to write this blog post. Just as I was about to start panicking the site came up again, however I was reminded of my group meeting this morning. In the meeting there were complaints about their tools not opening or giving error messages. Now Voyeur has been very picky about what kind of browser that I use with it and I do get error messages sometimes but they were easily dealt with. This, however made me get a glimpse of some of the frustration that my other group members have gone through in trying to access their tools. This for me exposes a major downside of the digital humanities. What is the point of having a tool to analyze text with, if the tool that you wish to use can not even be accessed easily and when you need to use it rather then when the server decides you need it.

Fingers crossed for the presentation everyone!

 

To have or not to have cheesy blog titles ; that is the question

Part 3: Filling in the Gaps

Continuing on from my last blog post, Words, words, words: Finding a Clear Focus, I’m still keeping my focus on Hamlet, the theme of madness, and foreshadowing within the play.  So far, I haven’t delved that far into using the other tools to help me further analyze Act 1.  Voyeur has been very handy in helping me discover most of my inquiries.  However, because Voyeur doesn’t separate speakers, I’ve been attempting to use Wordhoard to do this.  I don’t know if it’s Java or if it’s me but I seem to be having difficulties playing around with Wordhoard.  I have been using Wordhoard to find lemmas though which has been really useful.  Because I am focusing on Hamlet’s potential madness and foreshadowing within the play I decided to search “madness” and found the following results on Wordhoard:


So I know I am not using Wordhoard to it’s full advantage but it did help me find some useful quotes (which is sad considering the number of times I have read Hamlet ) that I had completely overlooked otherwise.  I searched “madness” and found the following quote: (Horatio) “which might deprive your sovereignty of reason and draw you into madness?” (1.4).  This quote demonstrates foreshadowing seen later in the play of how Hamlet uses insanity to deceive others around him and how Hamlet’s drive to seek revenge begins to make him act more insane, confirming Gertrude’s belief that he is mad in 3.4.  Even though this is a question for Hamlet, this is actually a question for the audience; his insanity becomes questionable within the play as it progresses making the audience wonder whether he is acting or not.  This quote is strong evidence (specifically if your focusing on act 1) on how the idea of madness develops throughout Hamlet and why it is such an important theme within the play.  According to Wordhoard, “mad” is used 22 times (only as an adjective and never as a noun) and “madness” is also used 22 times.  “Madness” appears the most within Hamlet compared to any of the other plays.

Even though I used Wordhoard to find this, I’m not going to lie, I could have just as easily used Voyeur to find this also.  For me, this is the hardest part of Phase 2, because I feel like Voyeur is such an easy and brilliant tool to use that I don’t know  how to fill in the missing holes with other tools.  So far, I don’t really feel like I have any specific gaps that need filling.  I was worried because I thought my old stubborn and lazy ways were kicking in similar to how I felt when first learning that we would be using Digital Humanities tools to analyze text but I really think Voyeur is one of the best!  Seeing the Phase 1 group presentations I realized some of the difficulties that the other tools brought which I haven’t had with Voyeur.  However, I have been using the collaborative method of Phase 2 by helping my group members with Voyeur.  Haha, do I sound like a Voyeur snob?  Feel free to call me out on it.

WAIT! We still have so much more to learn!

I started making some process, which was oddly enough not prompted by my tool. I became frustrated yet again with Voyeur because as I have been experiencing and learning about my team mate’s tools, I feel like Voyeur doesn’t really have anything new or special to add to the table (or at least that is how I see it through my eyes).  I was amazed by Jesse’s tool, WordSeer, and its ability to search for a person “described as”.  This prompted me to use Voyeur in a different way than I ever had. Instead of randomly searching words in Voyeur and or looking in the cloud for words appearing often, I decided to start reading the text in the corpus from Act three, scene 1 to the end of scene 3. I began to analyze and suddenly picked up on important words on my own.

As a starting point, we came up with a general theme.  Madness in Hamlet is portrayed in his actions or thoughts, conversation with Ophelia, the famous to be or not to be speech, and the play the mousetrap.  While reading the text I started to recognize certain words reoccurring under the idea of deceit, and the power of words (which i am saving for later 😀 ). 

Believe, hear and know don’t sound like special words at first, but the use of them are important. While reading the context of these words, I was immediately reminded of Shakespeare’s Othello and Iago’s lines, “I’ll pour this pestilence into his ear” (II.iii.330). The concept of pouring these deadly lies in Othello’s ear is directly reflected in Hamlet, both literally and metaphorically.  Claudius poisons Hamlet’s father in the ear, and uses words metaphorically to manipulate people and fill their ears full of lies (poison).

In our scene 1-3, know appears a total of 10 times, hear 8, heard 4, hearing once and believe 5 times.

While referring to the context of these words, believe was often used in terms of lies and deception by believing. For example Hamlet says: “you should not have believed me” and “believe none of us” at two different times.  In order to believe or know, one must HEAR or learn of it in some way. We all know that quote “seeing is believing”, well in Hamlet seeing and hearing apparently allows one to believe as well. Sadly, what they believe to be the truth is nothing but poison (more often than not at least anyways). Some of you may or may not find this interesting, but I thought these specific words were very important because characters relied so heavily on convincing characters of things, or fooling them with words.  Believe, hear and know are all closely related enough for me to make a connection individually, together, and in comparison to Othello.  Put aside Hamlet and Othello for a moment, it is interesting to think about how heavily we allow words, true or not (by hearing) to suddenly become something we quickly know or believe.

With this being said, I thought it might be interesting to take some of the words gathered from Hamlet and also submit a file in Voyeur of Othello to compare them.

Full Othello vs. Act 3 Hamlet

While inserting Othello into Voyeur, i learned more about my own tool. Apparently if you submit/ upload an entire play into the program, the results are a million more times interesting. Unfortunately, I kept getting error messages with Hamlet, but I thought some of you may be interested in what more Voyeur could offer.

Full Othello

Look at the pretty colors in the corpus reader! It also splits the play into scenes, shows the longest documents, lists distinctive words and shows the highest vocabulary density (ex, scene 2).

Back to work… although the characters within in the act of Hamlet rely on hearing or seeing to prove things, Othello the play relies heavily on characters not seeing things. This lead me to concentrate on the power of Hamlet’s words and language choice which help to drive his thoughts. While piecing together hear/know/believe with the power of words, I was also interested in looking into the connection between actions and words.

I guess presentations begin on Friday, and I can honestly say that Voyeur and our tools have so much more to offer than what we have already explored! I cant wait to share our findings with the rest of the class.

 

time to wrap this thing up!

It’s hard to believe we are already at our last blog post for Phase 2! The fact that we’ve all had access to 5 different tools for the digital analysis of Hamlet makes me feel like we’ve only just scratched the surface.  There are so many intricacies to these tools we are using (more than any of us can really understand with the limited amount of time we’ve been able to work with them) and it’s difficult to try and reach real in-depth results when we are simply familiar with the tools, not full-out experts.

It has been extremely helpful, however, to have 4 other teammates who can quickly answer the random questions that I throw up in the air just hoping someone will have a solution to.  Because each of us has extra practice with our own tool, we have found that we can help fill in each other’s tools where they seem to be lacking.  For example, Kate will ask, “can anyone search all the lemmas of this word?” and I can eagerly tell her that yes, indeed, WordHoard IS useful for something and that YES, it can search up lemmas!

It has been pretty cool to see where some of our tools align, and where some of them overlap.  We used a GoogleDoc to write down all of the things our individual tools are able to do, so that when we come across a specific need in our research we can check out the GoogleDoc and find out if any of the other tools can help us with our problem.  We have found this to be a pretty helpful way of going about things because without these lists of functions, I would have no idea what to even ask or who to ask about anything, and then we’d be getting nowhere.

So the subject I have been using the tools to study over the past week was how the aspects of the Ghost’s character may have changed from Act 1 to the rest of the play.  Because the Ghost only speaks in 2 scenes total (I figured that out nice and quick thanks to WordHoard) I realized I would need to branch out into the other tools to get some kind of information from these few appearances.  Turns out that Richelle’s tool, WordSeer, and Ruby’s tool, Voyeur, seemed to be of most use to me in addition to my own tool, WordHoard.

To start off, I used WordHoard to see how many times Hamlet talked about/talked to the Ghost.  I got six matches total.

From there, I decided to get help using WordSeer to get some visuals going for myself.  Richelle helped me create a Heat Map for the word “ghost” to see how many times the word even came up in Hamlet.  I got the following result:

As you can see, not only does the Ghost not appear in the last third of the play, but it is not even mentioned.  I got a sense of this from my WordHoard findings, but this visual helped me grasp the effect it had on the rest of the play.  I think the Ghost’s heavy involvement in the first Act really shows what kind of role it played in the story.  The Ghost comes in initially to give Hamlet a mission, lots of conversation is had about the Ghost between Hamlet and his friends, and the Ghost pops back in to check up on Hamlet, reminding him what it was he was supposed to be doing.  After that, the Ghost basically disappears.  Hamlet becomes consumed with what he needs to do, not for the Ghost, but for himself.  The Ghost almost seems to be irrelevant to his thoughts or topic of conversation after that.

Voyeur also gave me a similar result as the Heat Map, further enforcing my inference.  The Word trends function shows that all conversation had about the Ghost completely subside near the end of the play.

As far as the content of conversation surrounding the Ghost is concerned, WordSeer gave me lists of words of nouns, adjectives, and verbs that often occurred nearby the word “ghost”.

As you can see, words such as “life” and “death” occur most often out of any.  “Dead” and “blood” also seem to appear often.  By using this function that WordSeer possesses, it allows readers to find trends through the subjects that would be near impossible to discover without the tool!

Examples such as this have really helped me see what a fresh and important spin digital humanities has on the world of literature.  Tools such as WordHoard, WordSeer, Voyeur, TapOr, and Monk really do open so many doors in terms of research possibilities., things that close reading couldn’t ever really do. I realize this is a fairly new and ever-evolving concept, but I’m excited to see what else can be discovered in years to come in the digital humanities world.

Sound of Mind

I have struggled an incredible amount with my personal direction and how I wished to attack act five of Hamlet given the “endless possibilities” I have previously mentioned in blog posts, that Voyeur offers. That being said, it is surprisingly difficult to come to any concrete resolution about the fifth act of Hamlet because of Shakespeare’s wide vernacular and thus hard to draw comparisons with my tool. What I’ve decided to focus on for this blog post, lest I go insane with “endless possibilities,” is the questionable ambiguity surrounding Ophelia’s so-called suicide. I would also like to lead into the relationship of Ophelia’s death to Hamlet’s and how Ophelia’s death laid the groundwork for Hamlet’s final speech.
The rhetoric surrounding Ophelia’s death is very passive. Heavy usage of words that give way to her surrender to death, such as “incapable of her own distress” and “creature native…unto that element,” (4.7.2) suggest a far more unintentional death rather than suicide. The proceeding line “heavy with their drink” allude to act five when heavy is used only once more in the rest of the play when addressing the duel between Laertes and Hamlet.

Although this hypothesis is highly subjective, the intentional use of “heavy” in conjunction to “drink” when a multiplicity of words could have been used, can be regarded as an element of foreshadowing as “drink” is mentioned 10 times so closely to “heavy” and envelopes the death of the cast. Shakespeare may have intentionally threaded these words together so the connotation when the words presented themselves again would provide the same feeling of inescapable fate when they are each “pull’d…to muddy death.” (4.7.2)


Although Laertes and Hamlet exchange forgiveness and understanding and meet one another’s demise by poison tipped sword, Claudius’ intention of getting Hamlet to drink the poison as a backup plan is evidence once more of the inescapable design of his demise for even if he survived the duel he would be forced to be swallowed up by the drink. So too, does Gertrude meet her demise by said poison-filled cup and Hamlet’s insistence for Claudius to drink. Although each of these deaths can be viewed as murder, it is due to the play’s progression that it may just as well be viewed as each a suicide because of each character’s inability to move passed their pursuit of revenge. As a result, the deaths of surrounding characters that have no desire to revenge are mere casualties in male driven inertia to a damned fate. Ophelia’s death, although similar in vernacular to Hamlet’s death scene, is unjust and unintentional due to her secondary status and distance from the play’s central theme.
However, Hamlet cannot just be viewed as strictly evil in his blind rage towards revenge of his father’s death. He too, in many ways, surrenders himself to death just as Ophelia does as both are complacent in light of potential knowledge of their fate. Hamlet knows he will die if he were to but look at the circumstance in which he falls, much like Ophelia when she “fell in the weeping brook.” It is evident, however, that their misery was more inescapable than their death and so death is sweet because of it’s “silence.” The connection here becomes clearer in the table below.

“The rest is silence” finishes Hamlet’s life. King Hamlet dies with poison dropped into his ear. Ophelia continues to sing while she is drowning right up until she reaches her death…
In the image presented above, one can see that the final point in which Ophelia is mentioned in the play is also at the precise point in which “silence” is mentioned in conjunction to her name as well as with “good,” but not with “bad” nor with “music” or “sound.” Although this may seem loosely connected, the few times “silence” is mentioned throughout the play (5 times) it is mentioned always within the larger circle of “good.” This could prove the importance of Hamlet’s final speech as his life (from the start of the play) is filled with the ghost and the overwhelming flow of Hamlet’s contemplation being constant “noise” in his mind. Although he claims his madness is feigned, his contemplative nature suggests his mind is never quiet especially in times of distress, which would play heavily on even the most sound of mind. When Hamlet says “the rest is silence,” (5.2.370) there is a peace that he seems to embrace – King Claudius is dead, the man who poisoned the ear’s of men in more ways than one. In connection with his significant last words, Ophelia’s death is harolded with her singing melodious tunes and is finally silenced by death. Her singing, especially at a point when she is drowning and singing is clearly inappropriate, is perhaps metaphorical of her innocence which is in essence who she is and what she represents to each character in their affiliation with her. In hanging on to singing right up until the bitter end, she is defined mad. much the same as Hamlet’s defining characteristic is easily his contemplative nature which in displaying throughout the play has played a key in revealing to others his madness. He too, is contemplative right up until his death: until silence. the silence of death after so many words used to describe the chaos of noise is perhaps what makes this a comedy in the end term because everyone ironically is put to peace with silence. “Silence” although a selectively used word, is the key in this play.

Moving Forward

As this project progresses I find that it is changing the way that I view text and how it can be interpreted. By reading through Act 4 on my own and taking notes on it, I discovered that while the digital tools offer some assistance in breaking down the text into pieces and analyzing them as such, I still much prefer simply taking out the literature by itself and reading it on its own. Referring back to the forest and the trees metaphor I used in my last blog, by using the digital tools I find that you are staring so closely at the text that all you can see is the cells that make up the tree and the singular tree itself. However, by moving back and examining the entire forest you can look at how the different trees make up an ecosystem and look at other factors of the environment that have shaped the development of the forest and the individuals trees. Which view you prefer is an entirely personal choice, and it certainly exists on a sliding scale. My main experience that I am going to take out of this course is one of balance and appreciation that I have been introduced to these new tools.  I will use the traditional method to examine text and if I feel that digital tools could be used to further examine the text I am certainly not adverse to any additional context they could provide to the whole.

Now moving on to the project itself. The TaPOR member of my group  and myself have begun to collaborate using out tools to examine Act 4. Using the ‘Extract Text’ tool in TaPOR she will be able to extract only the speech of the characters using a much her program. This expedites the process quite nicely as the last time I edited a text it took far longer then it should have and I shudder to think how long it would have taken me to repeat the process on an entire Act as opposed to a singular scene. Once she has completed that, then I will be able to examine characters separate speeches and differentiate between the speaker and the spoken of. I have thought of examining the differences and similarities between Rosencrantz and Guildenstern, the way that Hamlet and Laertes act as foils to one another, (both lose their father under mysterious circumstances etc.) and examining Gertrude’s speech when Hamlet is with her and when Hamlet is not present within the same room. Hamlet’s back and forth with Claudius after he has hidden Polonius’ body is another interesting piece of the text to examine. Hamlet uses quite a lot of symbolism and metaphor in this scene and some have taken his patterns of speech to mean he is mad. When I originally read the speech I merely thought he was being witty and did not detect madness unit brought up to me by my then English teacher. At this point in this project myself and my group members are still feeling out one anthers tools and working on collaborating with one another. Hopefully we can comprehensively analyze Act 4 without becoming too lost in the trees and loose sight of the larger picture.

Knowledge and Knowing

Knowledge, in both its past and its present tense is a big topic in act two of Hamlet. Polonius is obsessed with the acquisition of knowledge about others, particularly Hamlet; on the other hand, Hamlet throughout a large portion of the play is seeking knowledge as to his uncle’s guilt relating to the death of his father, in fact his last soliloquy in act two ends with a plan that is intended towards the finding out of that same guilt. On this whole idea of knowledge and the gaining of it, the King and Queen also want to know something, what they want to know, is what exactly ails the young Hamlet.  The presence of surveillance and observation in Act II has been discussed a lot in my group and what after all is surveillance, but the gathering of information or knowledge.  Using voyeur’s Bubble Line tool I compared the words: Know, Known, and Knowledge; in doing this, I found out that the word know appears a lot more often than the other two do, it also appears in conjunction with itself in two points and in conjunction with knowledge in one point, whereas it is never in conjunction with known.  This leads me to believe that what is already known is not of the same importance as the desire to know things in Act II of Hamlet.

Above is the comparison of Know, Known and Knowledge using the Bubble Lines.

I also compared the same three words with the addition of the word, Unknown, using the word frequency chart, which in conjunction with the concordances tool on Voyeur is by far my favorite aspect of the program.  When I compared these four words I found that Known and Knowledge actually appear very close together near the beginning of the act.  I also found out the part of the act where the word Unknown is mentioned, none of the other three words that I searched for were mentioned.

Above is the Word frequency chart featuring the words: Know, Known, Unknown, and Knowledge.

From both the Bubble Line and the Word Frequency Chart, I have been able to glean that the word Know is used throughout the whole corpus of act II, showing that is definitely an important theme throughout the act and by its connection to the idea of surveillance and observation, I am fairly sure that it connects to my groups ideas regarding act II as well.

I had an epiphany :)

I have finally gained some greater insight to the benefits of text analysis tools. While referring to my first blog post from phase two last week, it was evident that I was struggling with the XML file. I tried again to figure out how Tapor works, but no such luck. So, after devoting hours and developing what feels like carpal tunnel, act 3 is completely hand edited.  Thank God Voyeur can do the rest of my work for me.

Let me say before I begin, that while being in English 205 last semester with professor Ullyot, I read Hamlet for the first time. I gained a surface level understanding. In attempt to analyze the text, In September, we flipped page by page, act by act while attempting to determine if Hamlet really was mad. Talk about old school. It wasn’t until this semester in 203, when I began to deeply analyze Hamlet with the help of Voyeur, that I gained all these great insights into the text. I just think it is amazing how a program is capable of analyzing the text, while bringing words, and other thought provoking ideas to the table. Sorry for the rant, but I am just amazed at my process of learning that these tools have evoked.

Now to be begin..

Act 3 is huge. We have the “to be or not to be” speech, Hamlet and Ophelia explore their relationship, some Guildenstern, Rosencrantz, Claudius, Gertrude, the players and the Mousetrap. In other words a lot of changes are made and a lot of drama begins. My first thought was revenge. Where does revenge appear in act 3? Well apparently not much. A total of 6 different times (revenge, revenged, revengeful). Not all that useful at this point. Today was a day in our meeting, where none of our programs could agree on the amount of times ANY word showed up.  In order to stay consistent, I put my faith in Voyeur.

Moving on, to begin the group focused on analyzing Hamlet and Ophelia’s relationship. There were two reasons for that:

  1. To define their relationship
  2. So we could determine on the same level, what each tool really could add to the analysis

Love was a word that was used 23 times between all of the characters appearing in act three. While concentrating on the scene where Hamlet tells Ophelia to go to a nunnery, Voyeur also picked up on the words honest and fair. However, Hamlet uses these worlds much differently than we do today.

Oxford Dictionary DefinitionÂ

I took the instances where honest and fair appeared and compared them while looking at their context. Since the box inside Voyeur is so tiny, i moved my information to word.

Copy and pasted honesty and fair side by side to compare

It was not until I looked further into Hamlet’s word choices, that I realized how often Hamlet used honest and fair. I have found recently that Hamlet constantly reiterates words as a way to either get answers from someone or to prove a point. Mad/madness is another instance in 3.4, where he keeps hanging on to this idea in order to prove to both his mother and himself that he is not mad. Hamlet’s unwillingness to stop hanging off ideas seems to be one of the biggest give aways to his ‘madness’.

Prior to analyzing Hamlet with the tools, I believed Hamlet had many reasons to act the way he acted. I never wanted to connect his actions to the assumption that he was mad. Again, with the help of the tools, by simply just analyzing Hamlet’s word choices and crazy tangents, its has become more clear than ever that Hamlet is mad. He is always scheming, and diverting his emotions off on to other characters.

Although Hamlet continues to treat Ophelia in a way less than what one would expect, it is interesting to see that Ophelia maintains her respect for him. After Hamlet makes a scene with the honest and fair ordeal, he starts up again and tells Ophelia “I did love you once”. Through the majority of the scene, Ophelia maintains her cool while using God and “sweet heaven” as external powers to ‘help’ Hamlet. Although she is concerned by his actions and words, she never turns on Hamlet or begins to treat him of a lesser value.

In order to further analyze Ophelia and Hamlet’s relationship, the extractor tool from Tapor would be very useful in separating these relationships from the rest of the play.

Words, words, words: Finding a Clear Focus

PART 2: Continuing on with the Plan of Action at hand and specific character findings

Continuing on from my previous post (check it out here!),  we decided as a group to focus on character development and foreshadowing.  I began to experiment with Hamlet and Horatio’s characters.  I broadened my experiment by comparing the specific words Hamlet would say and compare that to the context of what other characters were saying.  I was beginning to get frustrated because this was not giving me any specific results.  Today, during our group meeting, we decided to each pick a character and to focus on that character with our tool specifically ; discussing the pros and cons of the tools as well and how we could collaborate on Friday to fill in the gaps.  I decided to focus on Hamlet, Richelle will focus on Horatio, Dayna  – the ghost, Kate – Claudius and Gertrude, and Amy will focus on Laertes and Ophelia.  Similar to what I did with Act 1, I created another document of only Hamlet’s speeches, cutting out all of the other characters so that it looks something like this :

This way I was able to focus on what Hamlet was saying specifically.  Once I uploaded this onto Voyeur, I focused on the Word Cloud tool which gave me these results:

I noticed that sensory terms such as “eye”, “seen”, and “hear” are important terms as well as “reason”.  This is significant to the play because Hamlet is confirming what his senses feel in comparison to what he is seeing which relates to  deception – a larger theme within the play.  This ties in with the argument of whether Hamlet has actually gone mad or not in 3.4 when he can see the ghost yet Gertrude cannot.  Much of the first act gives us an insight into Hamlet’s reasoning and intellect.  In 1.2, Hamlet also foreshadows his father’s murder by Claudius when he says, “Foul deeds will rise, though all the earth o’erwhelm them, to men’s eyes.”  I found this quote when I searched the context that ‘eyes’ was being used in.  This line signifies a basis for the play because it also reflects Polonius’s actions when he creates lies to spy on Laertes and attempts to hide behind the curtains in 3.4.  I’m beginning to feel confident in this moment of Phase 2 because now my focus has become more clear and I am able to use Voyeur to my advantage.  In terms of the disadvantages I was going to say that the user cannot add words to the “Stop List”.  The ‘Stop List’ is a default list that takes away punctuation, conjunctions, numbers, etc., from the text that you upload so that you can have clearer results.  And like I was saying, I cannot add a word or remove a word from the ‘Stop List’.  But I was really shocked to find out that none of the other tools had anything similar to this so now I don’t see this as a disadvantage anymore.  I gotta say Voyeur has been pretty good to me – I just can’t look up lemmas.

New Beginnings and the Formation of POA

If you’ve been keeping up with Phase II Act I’s recent blog posts you will notice we have come across a new phenomenon called POA.  Thanks to my fellow group  member Richelle (check out her awesome blog post here!) we successfully came up with a focus for our group.  We will continue to discuss POA further on as we proceed with Phase II.  Now you might be asking yourself, what does POA mean?  POA is our plan of action.  POA is what will lead us to success within our second phase.

PLAN OF ACTION PART 1: The Obstacles

I used the xml file of Act 1 (click here to view!) and inserted it into Voyeur, my most valued tool.  Encoding words such as “xml”, “aker”, and “sp” were most used.  I went back into the xml file and, similar to what Katy did in the previous phase, removed all of the encoding so I could get clearer results.

However, I did not separate the speaker from when they are being the character is being spoken about. I discovered that Hamlet and Horatio speak the most throughout Act 1.  That seems obvious for Hamlet because he is the main character and also because he possesses the personality of an intellectual, constantly talking through each situation and calculating the outcomes, and also for Horatio because their [Hamlet and Horatio] relationship is established at the beginning. As a group we decided that the first act is where the characters are introduced and any foreshadowing for the play is revealed.  This seems easy, almost too easy.  And so we thought: what can we do with this exactly?  We decided the best thing to do would be to focus on character development in comparison to the rest of play.  Now that we have our plan of action in motion we can individually focus on our own tool and find our results from that.  In the next meeting we can then combine our findings and fill in the pieces with other tools that will narrow our findings.  For instance, Voyeur doesn’t allow me to separate the speaker from when they are actually speaking to when they are spoken about.  However, I can go to Dayna (the Wordhoard expert in my group) to do this.

What I decided to do with Voyeur was focus on one character, such as Hamlet for example, and focus on the specific words that they use and then compare the concept that the words are used in.  I think this will be a good way to show the character development when compared with the rest of the play.  So far, I focused on Hamlet and some themes that he is associated with such as “heaven” and “father”.  He uses the word ‘heaven’ often in vain compared the other characters such as Claudius and speaks of his father  the most within the first act.  Right now I’m trying to figure if I can compare more than three words at the same time from the Word Corpus tool.  The word corpus tool gives you all the words starting from most frequent to least.  I’ve noticed that if I flip to the next “page” of words that it gives me it erases the previous words I had highlighted on the frequency chart.  This is a little annoying but hopefully I can work it out with my group.

Phase II: New Group and New Beginning

I am rather excited for Phase II, not only because of the awesome people in my group but also because we now have the ability to examine more text in a more in-depth way. I found in Phase I that while Voyeur is excellent at testing hypotheses, Voyeur is not a hypothesis-generating tool. It is difficult to come up with ideas about the play unless you go through and read it yourself. It is this method that our group is going to use first. By first reading and examining Act 4 without the use of digital tools we can, (at least briefly) divorce ourselves from our computers and focus on the text. I found while examining Act 3 Scene 4 that I often focused very heavily on the trees rather than the forest, losing myself in the details without the ability to focus on the larger context of the corpus. Hopefully by reading and taking notes on Act 4 before hand, myself and my group can find common themes with which to work and remind ourselves of the forest.

One advantage of now having an act to work with rather than merely a scene, is now Voyeur has more words to analyze and work with. I feel that every group will attest to this advantage. While Act 3 Scene 4 was an excellent testing ground for our various tools I think we can all agree that it is time to move onto bigger fish. Using my beloved Word Trends tool I examined Act 4 and was presented with this graph…

Plugging in the words “good”, “death” and “love” I am now able to analyze themes within the Act. As you can see, “good” and “death” seem to mirror each other. This revelation and others will be worth exploring in further detail as Phase II progresses. Simply because the two mirror each other does not necessarily mean that the two ideas are actually related to each other. It is also worth noting that “love” ascends in the latter part of the Act as “death” and “good” showcase a simultaneous descending trend and then suddenly rebounding back upward. What is responsible foe this trend? As I have not re-read the Act yet, I am unable to draw a connection between what is actually happening within the Act to understand why this occurs. Again, this is a trend worth investigating further into Phase II.

I am really excited to collaborate with the other digital tools after watching their presentations. I think that by working together we will achieve a more comprehensive and through view of the corpus then we ever would have been able to do on our own with our own respective tools. At the beginning of this course, I came out of the tutorials with a premature judgement of each of the tools already made up. I had decided which tools I liked and which tools I didn’t like and it wasn’t until each of the presentations that I achieved a grasp of what the digital humanities actually operated. The only way to really gain results in the digital humanities is to collaborate and cooperate. It is certainly possible to gain results using only one tool to examine the text however I would not advise it. My hope is that through Phase II we will each be able to use our tools best qualities as well as being able to rely on the other tools to make up for our own programs disadvantages.

 

New Group, New Act

After our first meeting today, it hit home to me that although the Phase I and phase II are similar, this is not going to be the exact same as phase I.  This may seem like an obvious statement but, what I mean by it is, in phase I, we all worked on how to figure out our programs and to do so we used a very small piece of text from Hamlet.  In Phase II however, we are left to figure out a slightly larger, but still not very big, excerpt from Hamlet using the tools that we became proficient with in Phase I.  To me, this is the same assignment as before, but somehow opposite to what we did before at the same time.  In a cursory analysis of Act II, the thing that stands out the most to me is the fact that Polonius is a puffed up, arrogant, windbag.  According to Voyeur’s summary chart, Polonius has a whopping 68 different moments when he speaks, that is not counting his total lines, just moments when he speaks.  This compared to Hamlet who only speaks on 49 separate occasions in this act shows that Polonius talks a lot.

In discussing Act II with my group, we came to a few conclusions about the act together, among them were the idea that it is an act that involves a lot of Polonius’ bumbling and screwing things up, it is also an event that has a lot private moments that are made public, such as Ophelia telling Polonius about her scene with Hamlet.  There is also a lot of Surveillance and observation of other characters which lead Polonius to his fatal habit of hiding behind tapestries.  In comparing the four most commonly occurring words in Act II, which are: Lord, Good, Shall, and Say; I have noticed that all though all four of these words appear together in places, the words: Shall and Say appear together the most often and that all four of them appear together in the fourth section of act II scene 1.

I do not yet know if this will be overly helpful or if it is merely interesting, but it is what has been done so far by me in Phase II of this project.

I am slowly going crazy 654321 switch!

I had it easy, but I guess this is where my struggles begin. I don’t think I have hit any level of frustration dealing with these tools until now! I remember back in phase one, my biggest struggles was attempting to figure out how to log in to this blog business and post. Here it begins..

To begin I pasted in the XML file and expected to have some misleading information because Voyeur needs to have characters speaking split from characters names mentioned, as well as stage directions removed. I struggled a bit, attempting to copy all of act 3 into Microsoft word to edit it (LOL). What a mistake that was. I am sorry but 60 pages of editing is not going to happen. What was I thinking?

I know that Tapor has a tool that does this; however, after spending two hours reading phase one blog posts from the team, and also messing around with the Tapor tool, I was unsuccessful in my mission. I was however able to figure out how to separate speakers. Unfortunately I could only get Gertrude’s lines to work and she really only appears in 3.4 (which ALSO keeps including itself in our analysis of 3 to 3.3).

I was also able to figure out how to use the tool from Tapor that counts the caps. I think this is a really unique and useful tool, especially since it is able to pull out names that one would not think to search. For example Jove or God.

Although I learned some great things and not so great things about Tapor, Voyeur is my tool. I am forced at this moment to work with what I have, and what I already know. Until these issues can be ironed out, unfortunately I am using it as it is. I feel like the majority of the tools could be used as a starting point, while Voyeur will be one of the tools used towards the end in order to further our analysis. Therefore, I’ve concluded that my hypothesis to begin analyzing act 3, should be basic, while excluding anything to do with characters specifically (until I can get my issues fixed).

The word cloud! Hamlet is appearing in the biggest font. Thank god. Something is cooperating with me this afternoon.

YAY! RESULTS 🙂

Working off of the word cloud, love was quite a large word. Love appeared 28 times, while loves and loved appeared once.  This started to make me think about how the word love is used and how it changes throughout act 3 by all characters. This would also be neat to try it with other commonly used words! I found it interesting that “loved” was appearing towards the beginning. The word “loved” is past tense, meaning that Hamlet once did love.  The combination of the words love and loves appear later, but by doing so, it demonstrates a change in feelings.  If Tapor was cooperating with me, I could simply use just Hamlet’s line to analyze how his feelings change from his famous “to be or not to be” speech, to his confrontation with his mother in 3.4. Another tool that is capable of searching for synonyms or even lemmas to determine words similar to love would be useful as well.

 

When paralleling my tool to other tools, I think Voyeur excels in the ability to do comparisons. I was never one for the frequency charts or graphs, but I can see now how useful these aspects will be for phase 2. There are SO many other avenues that can be explored in act 3, that I didnt know where to begin. Act 3 is where a lot of drama begins and because of that, Ive been super overwhelmed! On top of this feeling of being overwhelmed, my tool has been giving me more problems than ever! Like i mentioned before, until I sit down and find ways to solve my issues, I am kind of at a stand still.

Seeing Eye to Eye

After a bumpy road of fiddling, frustrations, and findings – I believe I have broken through the surface of being worthy of the title “Voyant,” or perhaps as the french may call it: “voyeuse.”   Cheap jokes aside, I feel I have molded my mind enough around  Voyeur to be able to call it my specialized field above others.  Although I initially lacked this confident resolve in my previous post, continued meetings with a constructive team has seen me through to viewing Voyeur and Hamlet with a fresh set of eyes.
The tool enables a broad look at word connectivity within the text. Visual tools like “knots,” “word trends” (as examined in “Getting Off on a Bad Foot”) and “lava” provide a variety of mediums through which to display evidence in a specific fashion or equally varied to appeal to a broader user base. For each and ever self-contained “side tool” there is the option to either play or to read further into it so previous knowledge of any tool is completely unnecessary.   Our group met with more than a little confusion when attempting to analyze the mystery surrounding  knot interpretation.  After both playing with it individually and within group meetings we have come to a semi-understanding of the somewhat erratic knotting patterns.  Without the Hermeneuti information page, we would not have had any clue where to start in comprehending the tangling mess.  Any  way you choose to slice it, Voyeur is undoubtedly user friendly and that is potentially the key to what sets this apart from both its predecessor TAPor and as well from all other digital analysis aids.

As far as analyzing 3.4 has gone, the only obstacle I have encountered has been my own stubborn preference.  As a group, we have come up with several ways in which to tackle interpretation using our tool.  No matter which hypothesis we might have selected, we would have an ample amount of evidence supporting it due to our new understanding of Voyeur.
Some examples have been*:

  • Is Hamlet truly feigning madness or is it deeper than he fully understands?
  • Sexual tensions and the relationship between Gertrude and Hamlet – strictly familial?
  • What is the purpose of Polonius in this scene and why did his death come about in such an under-exaggerated manner?
  • Analysis of the presence of the ghost and the only tender picture painted for Hamlet and his dysfunctional family.

*Stay tuned to find out where we went with our brilliance…Coming to you, this Monday at 9AM (MT)!
On my own, I have played around with both aspects of scene versus entire corpus analysis and I far prefer examining the entire play and other plays/literary works in conjunction with  Hamlet. Although Voyeur has proven more than useful and enlightening to examine a specific scene and its advantages are obvious – my specific tastes lead me to seek wider horizons.  Perhaps my eyes are bigger than my stomach, however phase one has but whet my appetite for the main course next phase.
On another note, one of phase 1’s project requirements realized with the highest has been having been part  of such a reliable and hard working group.  There has been plenty I, and each one of us for that  matter, have put forward individually.  However, it would have taken a considerably longer time if we had not all pushed forward in united effort.  For every discovery that I have personally made using Voyeur, such as seeking out connections of good and evil and their escalating value within the play, I have had at least one peer add their discoveries to my own creating more concrete conclusions rather than theories. Past academic experience has proven a particular rarity in being placed in a group of such high work ethic and dependability.  Our communication is solid both inside and out of meetings and peer brainstorming is equally distributed and all opinions examined with respect.  Aside from newly acquired expertise, I would certainly  bring the copacetic nature that this group has exhibited forward into phase two.

What Could Be Better Than This?

As I mentioned in my previous blog post, I am not very technologically savvy, and because of that, I was very unsure about the use of technology in literary analysis.  For the first phase of our group projects, I managed to make what could be considered a terrible blunder by not attending the tutorial for voyeur, which happened to be the tool I am working with now.  Over the course of the last few weeks, I have discovered that Voyeur is an extremely user friendly tool that is very adaptable to the person using it.  I have discovered all that I have about voyeur with the help of my teammates, and simply by playing with the program and testing its boundaries.  The most common issue with voyeur amongst the people working on it is the redundancy of the tools in it.  Yes you have things like the word cloud called Cirrus and the bubble words which are basically the same thing except that Cirrus is much more visually appealing.  There are other similar examples of tools in Voyeur that are fundamentally similar, yet different, like the word knot and the word frequency chart, yes the Knot is more appealing visually, but the frequency chart is just easier to read for me personally.  The examples that I have just given may seem redundant, but they really are not, they are basically the same tool that has been altered so that it applies to different people and their respectively different ways of acquiring information.  However, I must agree with all of my colleagues regarding things such as the Lava tool or the Term Fountain.  I believe the sentiment was made in one of the comments on Ruby’s post that they look kind of like a piece of impressionist art.  It really is a valid idea that the makers of voyeur have attempted to put so much effort into visual learning that they have strayed beyond visual learning and into the field of art with something like this:

It actually makes little sense to me; there is no explanation of what the little bouncing dots mean, there is also no way to input parameters apparent to me unless you were to input a very precise file into the search box at the very beginning.  All in all, Voyeur is easily my favorite of all the programs with its simple interface right when you begin to use it; it has a very wide open site that is welcoming and pleasant right when you start.

I would have to agree with Dr. Ullyot’s sentiment that is kind of like Google, a simple search and go site right at the beginning.

From this point onwards, all a person has to do is enter a file in for them to search, and you instantly have several tools to analyze it right at your fingertips. What could be better than that?

Art Deco and Flexibility

While Voyeur possesses some wonderful tools for comprehending text, there are also some drawbacks, (although to be fair all of the tools have both their positives and negatives). Referring to my teammate Ruby’s post, (http://engl203.ucalgaryblogs.ca/2012/03/07/putting-aside-preconceived-notions-and-discovering-something-useful/) I completely agree with her about strange and redundant tools within Voyeur. The Knots tool was one tool that I specifically remember from the tutorial and I remember wanting to look more into it, however, I find using this tool provides little to no assistance in understanding a text. It is a tool for very visual learners and looks at the ‘path’ of words throughout the corpus and where they intersect with other words.

When you click on each “section”  of the knots, it takes you to where that word exists in the corpus. I find this tool to be messy and while it may be helpful for some people, my group and I agree that the Word Trends tool does the same job with more accuracy and less confusion. Other tools offered by Voyeur share the same issue, looking more like art deco then a comprehensive tool. Some tools in Voyeur accomplish the same task in different ways. Take for example the Bubble tool and the Word Cloud tool.

Bubble:

Word Cloud:

Both tools express the most frequently used words and organize them into a visual representation of that frequency. Now the main differences between the two tools are that in the Bubbles tool, there is a list of the top fifty, most frequent words in the corpus beside the visual and in Word Cloud the words are not separated and are expressed in different colours. One other difference is when you mouse over the words in Word Cloud you are shown how many times the word is used whereas in Bubbles that function is unavailable. Other then those minor differences, I find no real difference in function between the two tools. I personally prefer Word Cloud, however I would not mind some feedback as to why Voyeur developed what I find to be two extremely similar tools that accomplish the same purpose rather then developing a different tool that examines text in a different way.

Now it is not all bad. The Voyeurans and I have discovered many different uses for the tools that we do enjoy using and have discovered Voyeur to be a very flexible program which not only answers questions, but prompts new ones. I enjoy the freedom to examine different parts of the text on their own rather then being forced to examine the entire corpus/act/scene etc. For example, I can isolate the part of the scene when the Ghost is present and examine it separately from the other parts of the text where the Ghost is not present and look for differences between the two corpuses, (for example, whether certain words and themes appear more often or less often depending on the presence of the ghost). One complaint that I have heard from other groups is that it is difficult to separate the text you are trying to examine from the rest of the corpus. Perhaps during Phase II, this a way in which Voyeur can be utilized. I am looking forward to Phase II because I find that the more text you have to analyze the more interesting your results and being able to analyze an entire act rather then just one scene should lead to more comprehensive results from Voyeur.

Voyeur: my treasured tool

Before I begin, I’d like to mention that Voyeur is probably now become the world’s easiest program to use in my eyes. I even find managing my way around ucalgary blogs to be more frustrating and confusing than the ability to run Voyeur. Like seriously, half the time i cant find the log-in page. But on a more serious note, this journey for me has been very exciting. I come from the lands of creating HTML pages and working with Photo editing programs. This right down my alley 😉

Since my last post, I’ve learned some minor things about Voyeur that has opened a few doors to further my analysis. This is where I wish I could go back to my previous post and hit the delete button! One of the biggest discoveries was the ability to search a word within “words in the entire corpus”, while receiving a list of all the results, instead of a specific word that shows up alone in the “words in document” bar.  This could have saved me a lot of comparing and searching for words in stage one! The good vs. good night issue I had in blog post one, can now be scratched out.

While struggling to determine the weakness(es) of our tool, we concluded that Voyeur didn’t have a help button, or an explanation page to assist users to better run the program. However, shortly after, we blindly discovered the tiny little question mark in the top left corner of every box. How did we miss that? I do not know.  Although that may seem silly, when clicking on the button, some group members found that they were led to a broken link. This could be that, Voyeur, like a lot of other tools being used in English 205, are picky with browsers. I never had any problems with my browser (Firefox).

In order to further appreciate what Voyeur has to offer, we looked at some of the other blog posts and tools. Again, I feel like since Voyeur is SO user friendly, that it is probably one of the better analysis programs since it offers a variety of both visual and concrete data. Everything that a user could possibly use is located on one screen. Convenient, I know.  There is no need to flip back and forth between screens, and even the boxes of data can be minimized.

I feel by being limited to only analyzing 3.4, our group is running in circles, looking to take on much larger chunks of the text. I think that Voyeur will be more useful in the next stage, because we will be able to compare ideas, themes, and characters on a much larger scale. We came up with a lot of neat ideas that could not be used in this stage, since 3.4 is only a very small portion of Hamlet.

The tools in the customizable template have been a topic of discussion.  Prior to today, as a group, we concluded that the extra tools are too similar, and not very helpful in our analysis. Kassidy had mentioned that he even attempted to google the purpose of these visual tools and how they worked. No such luck. Ruby posted a few screenshots of the extra visual tools using the text from 3.4 here. Although many comments have been made on the useless of the tool, I attempted to prove that these tools were more than just pretty to look at.  I wanted to figure out when in the text this knots occurred, and why they were looping and intersecting.  I decided on the words HMLT, GRTE, mad and madness to keep my scope very small.

What the heck does this mean? Well by looking at this screenshot, it looks like nothing but a children’s art project.  When you click on the different segments of the lines, information is brought up. The pop up tells you the context of the word, but it fails to mention who spoke that specific line. So where do I go from here? By breaking down these segments into easier manageable sections, I concluded that Gertrude stating “alas, he is mad” was the beginning of this mad debate ( we already knew this though). Following this, both mad and madness are continually brought up by Hamlet.

Note: I made the version on left so i didn’t need to keep click on each segment. I thought this would be an easier way to figure out what was going in.

One flaw to this specific visual tool is that I don’t think a user would be able to rely solely on these images. I used a lot of background knowledge in order to assure myself that these conclusions were correct or at least on par. These images are good for understanding basic connections on how words or perhaps conversations flow, but the amount of time it took to break down the knots allowing for a conclusion, was annoying. Another interesting thing to note is why is it that Hamlet and Gertrude’s circles are different sizes when we know they speak equally 25 times?  With that being said, I don’t know if I failed at attempting to figure these knots out, or if I was really making something out of nothing , but at least I can say I tried.

On a more positive note, I am very excited to see what Voyeur can offer for phase two of group projects 🙂

 

Putting aside preconceived notions and discovering something useful

As my initial process with Voyeur comes to a close (or rather a new beginning) I can now securely say that I have entered into the world of digital humanities and embraced a new way of analyzing text.  Referring back to Katy’s first blog post of the traditional “cookie-cutter” method of analyzing text (go to Katy’s blog post here:\”Momentary Panic and Gradual Acceptance\”), I felt a little uneasy venturing into this unknown world of digital humanities.  I had no faith in my computer skills or how any of these tools would help me analyze text.  Now looking back, I have realized that suffering the long and tedious process of going through a text with only a pen or pencil in hand, is not the only option!  I find it ridiculous that I actually thought that the traditional method was easier. It was only easier, in my mind, because it was all that I knew.  I tested the water of digital humanities first with Wordhoard and was intrigued that I now possessed a single program on my computer that would instantly take me to any Skakespearean play I needed.

Don’t need to carry you around anymore! Ha Ha! :

But, I never took the time to make new discoveries about WordHoard and found it visually unappealing.  I gave up just as easily with the other tools; I assumed they would be just as uninteresting – and of lesser use.  Surprisingly, I ended up with Voyeur as my tool, which I knew least about.  Like I said in my previous blog post (check out my first blog post here!: “Initial Responses to Voyeur“), I thought it was only a bubbleline chart.  Yet now I was forced to look at this tool, figure out its purpose, and find a way to use Voyeur to help me discover new things about Hamlet.  And it wasn’t easy – until I let it be that is.  Once you find the right browser (avoid using Chrome and Safari – for Mac users) and get over the glitches of Java (as Nicole, my fellow group member will tell you, “it’s not your fault, it’s Java’s”) Voyeur has become one of the most useful online tools I have ever come across.

One of the major discoveries that I came across with Voyeur was that I realized it will take me to direct themes within the play.  My favourite tools became the Word Cloud, Word Trends frequency chart, and the Words in the Entire Corpus tool:

I began to correlate these three tools into finding different themes within Hamlet and how the terms were related according to how many times they occurred together or apart and so on.  When I was fiddling around with the program, I was inspired by Katy’s idea of taking a modified version of 3.4 and uploading it onto Voyeur.  I decided to go onto Sparknotes and then proceeded to create a copied and pasted document of 3.4 in the modern text version (check out No Fear Shakespeare for Hamlet).  I then compared the major terms in both versions, and also uploaded both at the same time and compared the two.  I am still looking deeper into this but what I have concluded so far is that the concept of “good” versus “evil” is a more evident theme in the modern text including the words “virtue”, “heaven”, and “devil”.

When you notice the repetition among certain terms and how they interlace you can then start asking deeper questions like I did by comparing the original and modern texts.  TAPoR is another tool that is similar to Voyeur where there is a word count (and other things I don’t know about yet until the group presentations!) but without the visual components.  For me, as a visual learner, the visual components are what make Voyeur special and interesting to play around with.  However, there are definitely some tools on Voyeur that are unnecessary.  If you didn’t see my previous post called “Are these necessary?” (check it out here!: “Are these necessary?“), I will explain – some of the tools are quite repetitive and appear almost “complicated” because Voyeur already has other tools that do the same thing in a more clear manner. For example, these tools (Word Fountain, Lava, and Knots):

all seem hard to read and understand.  Some of the comments I received on my previous post about these tools said they are visually appealing (maybe) but agreed that they are hard to understand.  So why have them?  Perhaps I should keep an open mind but so far I don’t see their significance!  As a group, we Voyeurans (can that be a word now?) found little use for not only the above tools I just mentioned but also some other visually confusing and also repetitive tools on Voyeur.  There is always room for improvement when it comes to technology.

Are these necessary?

  

I think my fellow Voyeur group members will agree, but the Knot tool, Lava tool, and Word Fountain tool (above) seem quite useless compared to the other tools on Voyeur.  I guess it provides an alternate visual representation of the text but to me it seems unclear and visually “messy”.  What do you guys think?

Starting Out With Voyeur

I came into this class with little to no knowledge about the use of digital tools to analyze texts.  To be honest, upon hearing about the use of digital tools in the humanities, I was a little bit skeptical of the idea because I was rather unsure of my ability to understand these tools and my ability to use them.  In using the Voyeur/Voyant tool, I have discovered that it is very user friendly.  For someone such as myself who has difficulty understanding many things on the internet, Voyeur is a surprisingly easy and user friendly tool.

By experimenting and basically just playing with the tool to discover what it can and cannot do, I have found Voyeur to be a tool with many facets, there are a number of different tools that can be used in voyeur for the purpose of passage analysis.  Items such as the word frequency chart, and the knot tool among others are there for people who possess a more visually oriented learning style; on that not however, Voyeur is not limited to people who are visually oriented, it also has tools such as term frequencies for both corpus and documents, as well as document KWICs (Key Words In Context).

Above are examples of Voyeur’s capacities for both visual analysis and written analysis of a text, in this case I was using both of these tools to compare Hamlet and Gertrude’s reference to his father.  The top tool seen is the KWIC tool and it is showing the words surrounding the word father, showing the context around the word, and allowing for a quick and easy analysis by a person.  The bottom tool shown is the Word Knot and it is showing where the words, Thy, My and Father overlap.  The Word Knot is a useful tool, but overall, my group has found the frequency chart to do much the same thing and is also easier to grasp.  Due to the work done so far in phase 1, I have gone from being quite skeptical about the idea of digital analysis, to being willing to try it and finding that it is both useful and enjoyable.

About the Developers

A few people have asked about the contact information for the developers of our various tools. As I said in class, remember a few things before you contact people for help:

  1. Describe your problem in detail, and ask clear and focused questions. Tell them what steps you have taken to try to resolve it yourself.
  2. Be polite and deferential. They are not customer service agents, but professors and experts who have devoted a lot of time to developing these tools and making them freely available to us.
  3. Give them at least 48 hours to respond; if you have nothing by then, take that as your answer or just keep waiting. Don’t send a follow-up for at least a week.
  4. Thank them for their time.
  5. Link to the course blog in your e-mail.

The Developers

Feel free to add other names of helpful people you’ve contacted in the comments; just make sure you tell us which program they were helpful about.

VOYEUR

  • Geoffrey Rockwell has a contact page on his blog. He is also on Twitter.
  • Stéfan Sinclair also has a contact page with a form, and here is his Twitter profile.
MONK
WORDHOARD
  • Martin Mueller is the contact person; you can e-mail him directly from the home page.
TAPoR
  • Rockwell, above, is listed as their main/only contact.
  • Kamal Ranaweera <kamal.ranaweera {at} ualberta.ca> manages user accounts.
WORDSEER
  • Aditi Muralidharan’s blog has her e-mail and Twitter details.

Getting Off on a Bad Foot

Admittedly, my first taste of Voyeur was tainted by it having been the only tool tutorial I had missed out on.  That having been said, I learned what I could from the video and web tutorials available online.  This was an immediate drawback to the tool for me as it all seemed very relative to previous text analysis tools and was presented it in somewhat of a bland fashion. In addition, the online tutorials created an image of an overly complex application of which the payout was not worth its difficulties.  In light of this, it seemed all too unfortunate that Voyeur, irony of ironies, was the tool assigned to me.
Post contract discussion and signing with fabulous Group D, I set about that very evening devoted to Voyeur and determined to unravel its bland mysteries…
As it turned out, Voyeur (formerly known as “Voyant”) has and continues to contribute to my more complete understanding of Hamlet.  Moreover, I was taken off-guard when I realized how entirely mistaken I was by labeling the program as “bland.”  As began to immerse myself into the aid and although it was a bumpy road in trying to understand how to achieve any analytical directives, I found myself enraptured with the endless possibilities of “word trends” and similar word frequency monitors and charts.  In the screenshot provided below, one can easily see how much you can read from the simplicity of searching the word “or.”  Squared off in red is the “segments” option where the user can select the amount of segments in which to stretch or squish the specific “revealed text,” in our case: Hamlet.  I have chosen 5 segments so as to better view my search results within the chart as Hamlet has 5 Acts, the math is pretty straight forward.
Additionally, squared off in blue in the same screenshot below, deeper exploration of the text is at the users fingertips as the “corpus reader” is open directly beside all of the companion exploration tools.  Aside from providing visualizations of the word frequencies, side blue bars of varying strengths guide you to the heaviest densities of your searched word.  Clicking on one of these bars (located to the left of the text) brings you directly to the specific segment in the play and highlights each searched word within the text.  Using the provided example “or,” in the blue square, a perfect example of the juxtaposition of the usage of the word.  Especially with the use of “or,” contrasting words like “heaven” and “hell” are set against each other and provide scrumptious brain-food for thought.  In my case, I was spurred on by this specific search and borrowed many of the opposing words I found and came up with some of my own, to discover what other secrets lie within the play.


When I met with Group D, we Voyeur’s shared our personal findings and experiences with the tool that we had discovered independently.  This added even more intrigue to Voyeur and its flexibility as  members of my group taught me additional pros, among them: it is completely customizable!  Aside from the website of origin, Voyeur has a site that allows users to blend their own skins depending on what you want to play around with or favoured gadgets (such as “bubblelines.”)  In the second screenshot, a simple breakdown of how this works is shown: just drag and drop!


As we’re all still experimenting with Voyeur, not all is uncovered yet.  However, as of yet the pros far out-weigh the cons.  Such cons being the bumpy road to discovery and some text visualizations rely heavily on java script: a highly fallible script reader, this shortcoming falling more so on Java and less on the program Voyant.
The experimentation has been more than entertaining with Voyeur, and as a result has already become my favourite tool, to my pleasant surprise.  Personally, I have a high preference for critical writing and analysis, and so the ability to broaden my own understanding of each play, act and/or scene is boundlessly amusing.  I look forward to discovering more independently and with my group.

 

Momentary Panic and Gradual Acceptance

Before starting this group project I was extremely hesitant about using digital tools to explore texts. Walking into class the first day, I was unaware of the digital humanities aspect of the course. I thought that it would be another run-of-the-mill english course complete with essays and when the digital aspect was introduced I will admit to being slightly taken aback. I was so used to the cookie-cutter high school approach to learning english, (read book, discuss book, write essay on book repeat) that this new approach to learning slightly scared me. Add two group projects and a twitter assignment and I am slightly ashamed to say that I became very dubious about the whole experience. However, through exploring my assigned tool (Voyeur) I am beginning to recognize the newfound advantages of the digital humanities and how we can examine literature through them.

Voyeur is an extremely nuanced tool with many different features for examining text. One of its strongest features is the visual element that it incorporates into nearly every tool that it offers. I find that the visual aspect offered to me by Voyeur allows me to experience text in a way that I otherwise would not have. Initially exploring Voyeur on my own the tool that caught my attention was the Word Trends tool. It divides the corpus you upload into sections and creates a graph showing either the relative or raw frequencies of words throughout the corpus. For example, (within Act 3 Scene 4) I looked at the relative frequencies of the terms “king” and “Hamlet” (When spoken by a character) and told Voyeur to divide the corpus into 10 sections. I achieved this graph…

Through this graph we can see when the subjects of “Kings” and Hamlet were discussed in Act 3 Scene 4, where they intersect and the rise and fall of these ideas throughout the scene. Through this tool I began exploring the frequency of other words throughout the scene and how the frequency of those words reflected the progression of themes and dialogue in Hamlet. This new graphical way of understanding text greatly appealed to me. In looking for other connections between words/themes I soon became frustrated with the XML file we had been provided. Voyeur takes the corpus as a whole and does not distinguish between Hamlet when referenced as a speaker and Hamlet when referenced by a character in the play. I created my own version of the text by copying and pasting the text from another source, making sure the text fit the version of the play we were given and giving “code names” to each speaker. To properly distinguish between Hamlet when he was speaking and Hamlet as referenced by another character, I gave him the code name Hmlt when he appeared as a speaker and repeated the process for Gertrude (Grte), Polonius (Plns) and the Ghost (Ghst)…

Using this system, not only was I able to separate speakers from speech, I was also able to track the frequency of each speaker though out the scene using the code names. For example, here are the relative speaker frequencies of Hamlet and Gertrude throughout the scene…

 

Those results are not incredibly surprising considering that Gertrude and Hamlet and the two main speakers within this scene however, it illustrates the flexibility of Voyeur and its ability to examine more then one facet of text. My group also discovered that Voyeur has a customizable layout where you can include different tools that are helpful to what you want to examine and exclude tools that are not quite as helpful. Overall I am beginning to warm up to this new style of examining text and hope to continue to discover more about Voyeur in the coming week.

 

 

My experience with Voyeur..

 

After experiencing a quick glimpse into Voyant after the workshop in class, my anxiety began to grow as phase one of group projects grew closer and closer to the start date.  After meeting with my group to finalize the group contracts, we decided for our next meeting that each member must find something new about Voyant. Overwhelmed with the complicated template of Voyant, I didn’t know where to begin. I didn’t have a starting point, a research question, nor had I had much experience.  I decided that I would work off something I knew for sure, the themes in Hamlet.

To begin, I enabled the stop list and was quickly surprised by the words which were most frequently used according to the word summary. Gertrude and Hamlet both showed up 25 times, good 10, bad 3, love 4, sweet 3, madness 5 and mad twice.  Not only is this list surprising, but it also demonstrates the themes and context of scene four. I wanted to further investigate the theme good vs evil. While referring back to the Hamlet textbook, I recalled this scene being a dark, less loving scene. So why words such as love, sweet and especially good, showing up so much more often than darker, evil words?

Voyant has the ability to search a word, click on the word in the frequency list (to further investigate its location), and it also shows the context of the word in its original sentence.  After further investigation, I found that “good” was appearing more often because Voyant was picking up on “good” in “good  night”,  which was used five times.  There went the support for my good vs. evil theme.  One downfall to Voyant already, is it picks up on words in the results that might not been expected.

Mad and madness in Hamlet is another huge theme of the play.  I wanted to look into who first used this word in the scene, who said it most, and I also thought maybe I could determine if Hamlet really was mad. I compared the two words, mad and madness with Hamlet and Gertrude, and I was surprised to find out that Hamlet uses mad/madness a total of five times, while Gertrude uses it once.  To me, this suggests that in this scene itself, Hamlet demonstrates he is mad by constantly hanging on to a comment his mother originally made.

Working off of mad and madness, I was led to question the validity of Voyant. Was Voyant counting mad in the word madness? After referring to the keywords in context menu, I learned that Voyant only searches for specific words you search for. This is a downfall to Voyant, as I mentioned before with the good vs. evil theme.  If you’re looking for more than just a root word, you need to specifically search words. For example, words ending in “ing” “s” “ness” etc. do not come up.

Although I have only mentioned the basic tools that Voyant offers, there are a lot of hidden visual options as well. At first our group was using Google to find the location of our additional tools, but with further investigation we found out each user is able to personalize their template by selecting or removing any tool. I found this to be very overwhelming, but these visual tools and extra options may be beneficial to those who enjoy tools such as word clouds, and line bubbles.

Custom Template Example

Custom Template

List of  Tools: the Google list: http://hermeneuti.ca/voyeur/tools

As Voyant at first seemed very difficult to use,  with time I picked up very quickly on the basics of this program. I am excited to see what more this program has to offer and what more there is to be investigated on Hamlet. My next step is to find a hypothesis or theme within this scene, which will become the basis of our presentation to demonstrate the advantages, disadvantages and use of Voyant.

Ps. The Voyant group is working off a custom version of Hamlet  — http://engl203.ucalgaryblogs.ca/category/ph1-voyeur/ Has another group found a way to separate characters speaking versus characters names being mentioned?

 

– Carly 🙂

Voyeur: My initial thoughts and responses in Phase 1

Before I began working on this project I did not look at Voyeur at all except in the work shop when it was briefly explained.  All I remembered from the workshop on Voyeur was that there was some sort of bubble chart and tree chart involved.  When I began to fiddle around with Voyeur (or Voyant) I quickly realized there was far more to Voyeur than a bubble chart.  My group and I discovered it was actually a median with sixteen tools that allows you to customize your own page to how you would like to analyze the text.  These sixteen tools are all very similar; they differ mainly by frequency and visual elements.  You just choose your own tools and create your own page.  So if you are someone who likes to compare words, characters, and themes with more of a visual component then you can customize the page to fit with your choice of visual tools.  If you prefer frequency charts and specific numbers, than you can analyze the text with the frequency tools.

Once my group and I began to explore Voyeur and all the tools on our own, we all found it to be very user friendly.  Words are easy to find and compare within a large text by clicking onto it in the text or chart.  Voyeur highlights each time the word appears within the text.  If you clicked on “love”, for example, in the word cloud or any other tool you choose to use, it instantly highlights the word ‘love’ each time it appears.  You can upload your own pdf files into Voyeur to analyze it or you can copy and paste the links.  Voyeur also allows you to take away any words you do not need.  For example, if you upload 3.4 of Hamlet, words such as “and”, “it”, “I”, and so on appear as most frequent.  However, you can take those words out of the text by using an option to do so.  This then allows you to see the important themes more clearly in the visual and frequency tools.

One of the major downfalls I found with Voyeur is that the program does not give you any clear directions to follow.  You have to play around with it and not get frustrated when you cannot figure something out easily.  Another disadvantage is that the frequency of a particular word might not be accurate.  For example, my group and I compared the words “good” and “evil”.  ‘Good’ appeared more frequently than ‘evil’ on the word cloud tool.  But when we looked at the actual pdf text we realized that Voyeur was picking up on ‘good’ in words like “good night”.  As you can see, this can be a problem because if we had not realized this we would have come to the conclusion that ‘good’ as a theme is spoken more often than ‘evil’.

My main goal now is to come up with a clear hypothesis to focus on in 3.4, similar to how we focused on the Oedipus complex in our Wednesday lecture, so that I can find out more glorious things about all that is Hamlet with the help of Voyeur. Here is a link to all the various Voyeur Tools that I mentioned.  You can see an individual image of each tool if you scroll down.  Check it out!

Voyeur basics

Voyeur (which was rebranded “Voyant” in 2011) is a suite of text-visualization tools, by the developers of TAPoR (Sinclair and Rockwell). Here is the material we will cover in our introductory workshop on February 10th:

  1. To learn this tool, begin with a “Quick Guide of Voyeur for Users.” It offers an overview of (1) how to get texts into Voyeur, and (2) how to view different kinds of results in Voyeur’s interface.
  2. The next step is to get texts into Voyeur. Here is a video explaining how to do that. We will work with these files of Hamlet.
  3. After that, you’re ready to view the results. Here is a video on the various tools that Voyeur gives you. Continue reading