The Digital Humanities and the Humanities: An Integrated Force?

With the accumulating significance of the digital humanities, comes the potential for an integrated, more effective approach to critical text analysis. The potential process arising from this rapidly developing field may be viewed as the following: traditional closed reading will provide the question, and the digital humanities will provide the answer, which may then be formed into a conclusion, following critical qualitative analysis to ensure the credibility of quantitative values. In other words, so long as human intellect is applied to evaluating  the validity of data, the quantitative approaches and results inherent to the digital humanities demonstrate the potential to illustrate new conclusions and questions regarding a text, through identifying patterns and trends which may not have been considered before. Throughout the duration of this account, it is my intent to convey how the implements of the digital humanities may be considered an equal part of the humanities, as opposed to simply an instrument to the broader field—so long as data and quantitative results are applied properly (with sufficient awareness of the potential sources of error in what is being represented). I will demonstrate this level of potential linkage, through first discussing a case study of Shakespeare’s Hamlet and how quantitative and qualitative text analysis may integrate with one another, before proceeding, in the second section, to convey the potential of the digital tool word seer to collectivize subjective and objective material into one unit, before later exploring the question posed by Michael J. Kramer in the blog post Reinventing the Wheel(which may be accessed using this link: ) that I have based my argument on, which is: to what
extent are the digital humanities one with the traditional humanities?
I will then proceed to highlight my reflections, in the final section, on
engaging with the digital humanities throughout the English 203 research-based course, commenting on what I have learned throughout the process.

Hamlet case study- A demonstration of how quantitative and qualitative approaches to a critical question may be applied in cohesion to form a conclusion

Upon evaluating the iconic text of Hamlet, two approaches may be pursued—an application of knowledge acquired through critically reading the text, or an alternative approach, in the case, being the use of a digital humanities tool to suggest trends and patterns that could serve as indications of plot, motifs, and character distinctions through speech patterns. In considering these two potential avenues for evaluating Hamlet, I have considered a question that is often debated, regarding the text: Can Hamlet’s perplexing behaviour be attributed to insanity(or “madness”) or to calculated deliberation? Qualitatively, Hamlet himself offers insight into his motivations for his later behaviour earlier on in the text in stating to Horatio, “Here as before: never—so help you mercy,/ How strange or odd some’er I bear myself/(As I perchance here after
shall think meet/ To put an antic disposition on)…”(Hamlet.1.5.166-70) before instructing his friend not to concern over his behaviour. Additionally, Hamlet also offers another indication that he is well aware of what he is engaging in, and how is conducting himself, when he subtly implies to Rozencrantz and Guildenstern: “I am but mad north-north west. When the/ wind is southerly I know a hawk from a handsaw”(Hamlet.2.2.315-16). How does this information relate to the question I posed? Critically analyzing Hamlet’s remarks for indications of deliberation exemplifies the qualitative approach to answering the question. The quantitative approach, which well supplements the qualitative
approach, may be conducted with a variety of digital tools—I am most familiar with Berkeley’s word seer(, and have therefore implemented it in my investigation.

While it is relatively simple to superficially label Hamlet’s term disposition as a façade or contrived attitude, there is little that can be verified about the statement, in the absence of knowing how the word is applied throughout the text. In order to find out exactly what “disposition” refers to, I found it suited to input the word into word seer’s word frequency heat map function( feature=endscreen&NR=1&v=DPhQQExQjZ4) which enables one to visualize the frequency of a word throughout a text, and identify when exactly it occurred(I will elaborate further on the potential of this feature in the next section) in order to observe the different meanings it represents, and how often it is used. In conducting this assessment with the entire text, I received the following results:

Incidentally, the word “disposition” sparsely occurs throughout the text.  However, in the usage of the word pictured in the above heat map, it appears once again to represent either personality traits, or characteristic tendencies—aspects that could feasibly be manipulated, or otherwise “forced”, as Hamlet is described as doing. This is an effective example of how quantitative figures may reinforce or reaffirm hypotheses or qualitative speculations. While this data is intriguing, I decided to consult another feature of word seer, the word tree function, to see if I could identify the context surrounding the word “disposition”, each time it is used throughout the text. The results I received are as follows:

What I found interesting was that the word truant appeared in the context of one of the uses of “disposition”, another apparent indicator of disposition derived from a tendency. Therefore, a potential answer to the question I posed, harnessing ammunition from both qualitative speculation and quantitative results, could be that Hamlet is well aware of the way in which he is prepared to conduct himself, and is thus entirely sane, and is concocting a ruse to mislead his uncle from his intentions—a deliberative, conscious act. While this assertion is open to re-evaluation, and is not necessarily correct, it provides an optimal example of how the qualitative and quantitative can intermingle to produce new conclusions, or otherwise reaffirm them—a product of the digital humanities and the larger field of humanities integrating.

Word seer- An efficient companion to my research

Berkeley’s word seer, a relatively simple to use instrument, is most useful in its capacity to transform raw data into new questions. What I mean by this is that the tool demonstrates  the potential to reinforce or generate qualitative hypotheses, based on quantitative data returned—as, when one employs word seer in their research, they are often not sure as to what they will find. In a previous blog post( I discussed how word seer is both interesting(through its visual qualities) and insightful(in its potential to produce new interpretations, or disregard obsolete preconceptions), and how superficial suppositions(such as Hamlet being considered about “death” or “revenge” alone) may be discredited based on the actual word frequencies of such words, as revealed by word seer. For instance, in regards to the qualitative value of the tool, my initial observation(expanded upon in my blog post cited above) was that “…a constantly recurring word can be inferred to represent a central theme within a text, as a word such as ‘lust’—one carrying thematic implications—may recur in one of Shakespeare’s other texts…”. However, the perils of accepting these words as themes without critical analysis and the application of human
intellect is illuminated in Michael J. Kramer’s admonishment that “…even as we find ourselves experiencing the new, it’s just as worthwhile to locate Digital Humanities in relation to the old.” In this case, the “old” is traditional text analysis, which must not be neglected, even though word seer and its aesthetic visual qualities(such as heat maps and word trees) offer an intriguing alternative. This is yet another example of how the quantitative and qualitative must work in cohesion—in this case, mutually offering insights towards one another, as data may prompt new questions, which may then be viewed through a closed reading lens, considering specific thematic and plot aspects of a text.

In responding to my assertions of the methods that must underlie the tool word seer, one might contemplate this question: What evidence is there that word seer can aid in disregarding obsolete or superficial qualitative conclusions or hypotheses, surrounding a text? My rebuttal is illustrated in this search of the frequency of the words “revenge”, “murder”, “death” and “kill” in Hamlet, using word seer’s heat map function, with the results depicted below:

Needless to say, Hamlet’s earned legacy, coined by popular culture, as the revenge tragedy is supported by the frequency of the words I selected, as they appear abundantly throughout the text. However, perhaps Hamlet isn’t exclusive to the characterization of “revenge”, as a conducted search of the same words in Coriolanus uncovers somewhat similar results:

These word frequency similarities may serve as a prompt for a qualitative investigation, based on this quantitative data, into what plot elements of each text establish Hamlet and Coriolanus as similar—another testament to what kinds of questions and approaches can be provoked by synergy between quantitative and qualitative methods.

In another of my previous blog posts(, I evaluated, in great detail, the extent to which word seer may aid in determining whether or not Hamlet as a character fits the profile of a tragic hero(compared with the flawed characters of Shakespeare’s other texts, such as the ambitious Macbeth)through the use of its described as function, which enables one to view the words used to describe certain characters by those around them. In inputting Hamlet described as “blank” I received support for my hypothesis that Hamlet is not as well
defined as other tragic heroes featured in Shakespearean texts
—if a tragic hero at all. Qualitatively, he lacks the tragic flaw that causes him to pay with his life for a mistaken act(while Hamlet dies, it is not directly the result of something he has done based on a flawed character trait, as opposed to say, Othello, who commits the mistaken act of murdering his wife Desdemona as a result of his tragic flaw of envy, and then ends up taking his own life as a consequence), while quantitatively, the data of word seer reveals that he is described as the following(which are hardly terms indicative of a tragic flaw, or character weakness):

In essence, these correlations between a character and how they are described are valuable in indicating not only how they are perceived, but perhaps how they act as well. Therefore, in light of word seer’s ability to perform such searches, along with heat map and word tree visual representations of word frequencies throughout entire plays(or even more compact fragments of acts and scenes),   deems it a formidable and useful implement of the digital humanities. Not only has this tool allowed me to engage substantively with the text of Hamlet , examining details that are often largely overlooked or obscured in the process of traditional closed reading, but also, it has provided me with a medium to blend critical qualitative text analysis with valuable trends and patterns identified by quantitative data. Thus, not only is word seer an effective tool for viewing word frequencies and conducting word comparisons using the simple search feature, it is also an agent of blending the subjective with the objective, in order to aid in establishing new avenues for research. It supports the claim that the digital humanities and the humanities can, and should be(with careful attention being directed towards the quality of data received) a unified force, as opposed to one “serving” the other.

Further exploring the question: Are the digital humanities and the humanities one?

An integral consideration has been articulated throughout this account: that the digital humanities and the traditional humanities are an integrated force—not a superior and subordinate. However, I have also advocated that there are potential hazards to relying too much on data, without stopping to consider its implications, or its possible errors or misleading aspects. I have based this argument largely off of Michael J. Kramer’s Reinventing the Wheel, in which he effectively conveys the responsibilities that are inherent on behalf of the searcher when consulting data results, in his admonishment that “The danger here is that we are not thinking carefully about the framework in which Digital Humanities
might thrive and contribute to society beyond assumptions about technology solving all problems…” This is a highly impactful statement, as it highlights the tendencies, when the digital humanities and their associated tools are enlisted, for users to either uncritically accept data as the truth, or otherwise, dismiss the value of data to the humanities, altogether. An excessive faith in technology, as in other fields, such as science and environmental politics, may often lead to overconfidence in its ability, causing critical concerns and issues requiring intellect to be largely
overlooked. An example, in terms of the English 203 research course, would be accepting the data of word seer and its word frequencies extracted from Hamlet to represent the theme of the text, and the overall message, without closed reading to identify the integral context of the play. While word seer, in revealing words such as “death” to be frequently occurring throughout the text, may allow one to develop the opinion that the play largely circulates around death and murder, without the context achieved through reading the play, these artificial suppositions are virtually meaningless, as these words could conceivably occur frequently in a comedy about love, as well. In other words, data without a context is merely an assumption, even if it closely represents details that are consistent with the theme of a literary work.

“We can be critically self-reflective and move forward,” are Michael J. Kramer’s optimistic words, regarding the digital humanities. This belief conforms to the idea expressed throughout this post, that, with a sufficient amount of critical guidance and thought, data and context or qualitative textual elements can be intimately joined with one another. Kramer consistently articulates the importance of retaining the methods
of critical thinking in traditional textual analysis, well exemplified through his observation that “…there’s nothing wrong with being excited about the fresh, unprecedented, and surprising places that the digital takes us, so long as those are not placed in direct opposition to the rich past of humanities scholarship that we can draw upon…”. In other words, the digital humanities and the broader spectrum of the humanities may be joined, and data has inherent value, so long as it is evaluated through the critical lens of traditional textual analysis methods, such as careful and
rigorous rereading of texts.

Reflection on the English 203 Course and Conclusion

The fundamental concept that I learned throughout the English 203 course was that nothing is complete at face value—different interpretations exist, and new approaches, such as the use of digital tools, are necessary to furthering understandings of texts, in this case, Hamlet. Critical thinking has been a staple aspect to this course, as, when one is consulting data, they must be aware of what it implies, and how it can be applied to form conclusions. This course has also been instrumental in improving my digital literacy, as I am now able to more readily apply word seer to my research, for near instant results. Additionally, the course has encouraged me to consider the impact of qualitative details within texts more
carefully—ironically, the incorporation of data into my studies of textual analysis has helped me to better understand the importance of words, and how they are dispersed throughout a text(such as the potential significance of the word “disposition” to Hamlet’s behaviour, discussed earlier.) I am now more open-minded in regards to the potential for digital tools and data to supplement closed reading, so long as the two approaches are applied in unison with one another.

To briefly reiterate my argument, based upon the blog post of Michael J. Kramer, and my experiences and work throughout the course, I have concluded that the digital humanities and the humanities, and the quantitative and the qualitative  may blend with one another
to form a cohesive unit, so long as critical thinking is applied to addressing quantitative data that is retrieved using digital humanities approaches.
I then aimed to reaffirm this assertion with a Hamlet case study, a description of word seer’s  potential as a digital tool and its capacity to join the quantitative and the qualitative, and the prospects of the digital humanities and the traditional humanities being
considered as one—similar to the view of Michael J. Kramer, who effectively depicts the relationship as “…not a revolution away from the humanities, but a turn more fully into the humanities.”


Works Cited

Shakespeare, William. Hamlet.  Ann Thompson and Neil Taylor: London, 2006. Print. The Arden Shakespeare Third Series.



Defining Hamlet as a Tragedy, or Lack of One: A Quantitative and Qualitative Endeavour(Phase Two, Blog Post Three)

*Note: Due to time constraints, this is my third blog post due for Monday, March.26, submitted early.

As the basis of my research, regarding the fifth act of Hamlet, I have fixated my efforts around one fundamental underlying question: What is the significance of act five of Hamlet, alone, and how does it define this iconic play as a tragedy? I explored this question in my previous blog posts, however, I will now, through this account, elaborate on how I have further employed my digital tool word seer to pursue a tangible answer to this question. As I continue to familiarize myself with the vast array of possibilities and enticing functions offered by the digital tool word seer, my confidence in digital humanities approaches formulating new conclusions and raising new observations regarding familiar texts is increasing
as well. For instance, now that I am able to segregate just the fifth act of Hamlet,  I am able to isolate it as its own distinct and significant entity, and thus, I am able to produce conclusions and hypotheses regarding the single act alone, as opposed to the entire text—a process not as easily accomplished with traditional text analysis and closed reading. Therefore, in my last post I explained my preliminary trials of inputting words from the fifth act of Hamlet into word seer and observing the returned usage frequency results on the heat map function—results I was highly surprised at—and will, in this post, explore how word seer and its comparative features may be implemented to suggest provocative details about the text, such as sudden escalations of the frequency of a given word at a given instance.

One of my primary considerations, regarding Hamlet, an assertion that I have implied in several of my blog posts, is that the play does not appear to confirm to the superficial niche that tragedies are often classified under, in terms of words used. In my last post, I discussed how words such as “death” “loyalty” and “fall” appear remarkably less frequently than I had initially anticipated, prior to conducting the search of act five in word seer. To exemplify, in terms of word frequencies, that the fifth act of Hamlet is relatively sparse in words that one might expect to pertain to a tragedy, I have included results from a test that I conducted using some of the words that I have previously inputted in a search of the entire play, as well as some new words such as “beast” and “wretch”. Upon viewing the results, one will quickly conclude that Hamlet is lacking in these words, leaving room for qualitative speculation as to why this might be.

The same search conducted, this time using the entire play, returns a greater frequency of the same words, yet, not to an overwhelming extent (the results are featured below). Additionally, in carrying out this test, I have satisfied the aim of my previous blog post, which was to apply word seer to compare the frequency of the same words between the fifth act of Hamlet, and the entire text.

Therefore, one is left to infer that in terms of language, Hamlet is variable from other Shakespearean tragedies. Seeing as to this quality, I am
armed with a more quantitatively geared set of evidence in my argument that the so called “revenge tragedy” isn’t much of a tragedy, after all. Of course, when I refer to the term “tragedy”, my evaluation adheres to Aristotle’s classic conception of the genre: I do acknowledge that I have largely concentrated on this definition of tragedy throughout the entire research process of this course, however, I believe that I am well justified in having done so, as Macbeth and Othello—tragically flawed heroes in possession of Hamlet’s lacking “cue for action”—pay dearly for their mistaken acts, acts of which, unless one considers Hamlet’s accidental slaying of Polonius, are largely missing from the play, and not only that, Hamlet is not the only character to pay the price in the end of play. I have highlighted these details so not as to embark on a subjective tangent about the play’s qualities, but rather, to uncover what details digital tools and word frequencies may aid in identifying. Therefore, in conducting the word frequency tests that I have(using word seer) I have searched for meaningful trends, such as repeatedly recurring words, that could potentially suggest the theme of the text, and thus, I could compare these supposed themes with my own standards of what defines a tragedy in order to assess how well Hamlet conforms to the profile of the genre.

However, despite all of these possibilities, I still have, as of yet, to uncover the significance of  act five, itself. Still, I have employed some new methods, using different features of word seer to establish whether Hamlet himself fits the profile of the tragic hero, especially in the final act of the play. In order to do this, I aimed to see how he was defined by other characters in act five, through inputting Hamlet described as “blank” in the related words feature of word seer, and received the results pictured below:

If I were to evaluate Hamlet’s overall level of compatibility with the conventional tragic hero( such as, for instance, Titus or Macbeth) I would certainly consider these results to deviate from the profile. I would have expected words more in accordance with “vengeful”, “wretched” or “rash”, or perhaps synonyms to these terms. Yet, Hamlet is referred to as “young”, which in itself, is not a sufficient tragic flaw. Therefore, on this very subjective, qualitative basis (as an interpretation of quantitative data) I will conclude that Hamlet is, at the very least, not a well-defined
tragic hero. How does this relate to my original posed question? In actuality, searches such as these have led me a somewhat different direction, however, I do find myself armed with an adequate conclusion to answer my underlying question, which has guided me through this phase of research. How is act five significant from the rest of the play, and how does it define the play as a tragedy? Using evidence from my closed reading I will advocate that the fundamental action and exhilaration of the play culminates into act five, serving to establish it as significant on its own, while I will argue that act five defines the play as a tragedy only through its outcome, and not its other plot elements, or word frequencies. Therefore, once again, I have found that my conclusion formulating process has largely compiled both quantitative and qualitative features, and both data and interpretation, using both my personal perspective regarding my experience with the text, and the numerical patterns achieved through my digital tool to render both generalizations and specific statements about the significance of act five of Hamlet as its own unit.


Word seer and the Final Act of Hamlet: Continuing to Narrow the Focus (Phase Two, Blog Post Two)

In continuing to research the text of Hamlet, while employing my tool of expertise, word seer, I have aimed to establish any potential discrepancies or factors that render the fifth act, my group’s act of study, as more “tragic” than the other acts of the play, or otherwise, the only
truly “tragic” act, alone. The focus of my previous post was to fixate on the distinction between my own interpretations, attained through critical closed reading text analysis, and those of word seer’s, while now it is my intent to narrow my scope even further, in concentrating my efforts towards what qualities—both  quantitative and qualitative—define the fifth act of Hamlet as significant as a single entity. In other words, my exploration of the text, both through traditional reading and digital assessment, will be geared towards uncovering clues or evidence to suggest how act five both differs from, and unifies the rest of the play, at the same time. Therefore, I will focus less on the digital tools and how they operate, and more so on the results they return, and how they may be implemented to suggest new conclusions and avenues for research.

My first objective was to segregate act five from the rest of the play, using word seer, and upon further learning how to do this, I will thus evaluate (using the functions of word seer) the comparison between act five, and the rest of the play. This will be my preliminary assessment, and I anticipate that I will have a sufficient indication of what words in act five will outweigh others used throughout the text, which could serve to exemplify certain trends worthy of further investigation, such as increased frequencies in one word that could potentially suggest the development of a motif that pertains to either the plot, theme, conflict, or tone of the text—all valuable quantitative fixtures with the
potential to support or discredit qualitative hypotheses. However, while I am still in the process of determining how to compare the whole play to act five alone, out of respect for the deadline of this post, I concentrated my efforts more towards seeing what I would be able to uncover from a word frequency analysis of the fifth act, alone. Therefore, my first order of business was to expand upon what I began in my last post, which was inputting the words, “soul”, “duty”, “life”, and “death”—words that I feel pertain to a revenge tragedy. last time, however, I was unable to isolate just the fifth act of Hamlet, and therefore was only able to observe how these words were concentrated throughout the entire play; now I am
able to determine their significance within my sphere of study—a large leap forward, in my estimation. The results of my search are featured below.

To my surprise, these words occurred in a relatively sparse concentration, thus, prompting me to consider alternatives in characterizing the theme of the text. I am pleased to comment, as a side note, that now that I am able to work with the fifth act, alone, I am more comfortable, and may be more efficiently discriminative in my research. Therefore, in response to my unexpected results, I felt obligated to try the same assessment once more, this time using the words “die”, “fall”, “revenge”, and “damned”, all words that may also be implemented to characterize both the theme and mood of Hamlet(this procedure is featured below).

Again, much to my surprise, these new inputted words demonstrated similar effects to the first set of words I worked with, although, to an even greater degree. What was most striking is the fact that the word “revenge” is only featured once throughout the entire final act of the play, which leads me to further infer that often the words most frequently associated with a text may not be the most appropriate or commonly recurring. Such changes in word frequencies, as my group colleague Stephanie explored in her blog post—in which she discovered that Hamlet’s motivation for revenge appears to wane towards the end of the text(as he refers to his father less and less)—may be used to raise new qualitative questions such as, “what is really is the number one thing on Hamlet’s mind as he nears his final confrontation with his uncle Claudius?” Stephanie’s work may be observed here:

Therefore, what I was able to obtain from these two assessments was a reaffirmation of my previous theory that, when considering text analysis, digital methods must be examined through a critical scope, while still serving as effective in shattering perhaps invalid preconceptions, such as how I initially believed that words such as the ones that I inputted were infallible in characterizing the themes of the text, whereas, I now recognize that I can employ word seer in a trial and error process of inputting new words that I think of in order to determine which ones could be implemented more effectively in describing the text as a whole, and more specifically, act five. Therefore, I will continue along with this inductive process, in aspiration of uncovering a new, insightful conclusion about both which words best define the fifth act, and what defines
the fifth act as a significant unit on its own, from a perspective of word frequency and usage. Essentially, I feel that the discovery of how to isolate
the act in word seer will greatly facilitate my research process, and I am quite pleased with it, to date, and will therefore continue to explore its
benefits as well as my new findings in my next blog post. In other words, I have narrowed the scope in this account more so than my previous post, and I attend to narrow it even further in using word seer, now that I am becoming more familiar with its functions.

Death, Death, Death- Or is that it? (Phase Two, Blog Post One)

Throughout the course of this post, it is my intention to explore the relationship between my interpretations of the text of Hamlet acquired
through traditional text analysis and my closed reading of the text, and the interpretations drawn from employing my tool of expertise, word seer, to critically analyzing certain fragments, in this case, a single act of the play. I will then highlight how these two approaches compare to one another, and pose further questions as to how this comparison may be capitalized upon in order to generate new conclusions or insightful observations.  I would first like to express that I have always been sceptical of classifying Hamlet as a conventional tragedy, as the protagonist Hamlet deviates from the characteristic traits of the tragic hero, and commits no apparent “mistaken act”, and the majority of action does not culminate until the bloodbath of act five, coincidentally, the act I have been assigned to study. Therefore, my interpretation of this act can largely be characterized by the observation that it alone defines this iconic play as the tragedy it has come to be widely recognized as. Without summarizing the plot of the text, it is evident that the catastrophe and other defining aspects of Aristotle’s conceptions of the genre
of tragedy are reserved almost exclusively for act five, as Hamlet and a series of characters surrounding him, including the villainous king Claudius who he seeks to exact a vendetta upon, face their untimely demise. So what does this mean to my interpretation? Death, death, death. Futility, futility, futility. Basically, I believe that the bard is trying to express to us a message that revenge only manifests as death, and highlights the futility of life the struggle associated with it. My interpretation is one among many, however, of course. Even as superficial a source as Wikipedia recognizes a multitude of proposed and perceived contexts and themes that the text carries.

Now, this interpretation is just fine, on a superficial, redundant, basis. However, when we seek to uncover new insights and avenues for exploration that have rarely been embarked on, it is also effective to employ tools such as word seer to aid in identifying new trends.

So, how would I gauge word seer’s interpretation of act five of Hamlet, and, in turn, compare it with my own? In considering the advantages of word seer that my group outlined during phase one of our team assignments, I felt obliged to plug in some words, pertaining to act five in particular, that I felt could be conducive to word seer’s processing. Simple enough, right? However, this was not the case; incidentally, I was unable to segregate the fifth act of Hamlet alone(a task I will fixate on more as my research progresses), therefore, I felt it fitting to exhaust the next best alternative, in examining the entire text again using word seer, in order to apply it more broadly to my interpretations of act five, alone. I must comment, of course, that this may be an instance in which another tool, such as voyeur and its image qualities, could well supplement word seer’s shortcomings. Regardless, I decided to employ words that I feel characterize the themes of Hamlet, and proceeded to observe the concentration of them throughout the text, paying particular attention to the words that more frequently occur towards the end of the text, that being, act five. In this case, I searched “death”(as a fundamental), “life”, “duty”, and “soul”, in order to observe whether or not they appeared heavily towards the text. (These results are pictured below). However, what I was surprised to find was that these words, which all carry emphasis within the “revenge” tragedy, were dispersed throughout the entire text, and did not exceptionally exceed their counterparts near the end of the play.

What exactly did I make of this? Ironically, this interpretation provided by word seer, identifying that none of these words completely define the text in frequency, contrasts to my own closed reading and textual analysis interpretations in demonstrating that words themselves do not necessarily develop into a coherent indicator of theme. Therefore, I am intrigued towards studying speech patterns and speaker frequencies in order to expand my perspective regarding interpreting Hamlet, a process which, I will conclude, could be better achieved by other tools.

Before giving up on my previously advocated frequent words constituting theme theory, I intend, one last time, to compare “death” and “honour” with the other texts in the Shakespeare corpus, in order to see if the frequency exceeds the other texts, perhaps suggesting that Hamlet is founded more on characters, speeches, and themes that favour these words. For now, however, I will reiterate the relationship, and comparison, between my interpretations of Hamlet, and those suggested by my findings in word seer.

It would be an exaggeration to suggest that the two interpretations I worked with were at dueling odds with one another. While word seer’s findings didn’t exactly support my interpretations, (the results would have verified my interpretations were they to contain a higher concentration of the inputted words near the end of the play) they certainly aided me in recognizing that interpretations and perspectives should not be taken at face value, in that, words that are suspected to occur frequently do not constitute the theme of text. Therefore, while my interpretations are geared more towards my closed reading, the word seer interpretations helped me to be aware of leaning towards
one theory or conclusion without considering varying alternatives, and this is the ultimate underlying relationship between what I found and suspected, and what word seer supplemented it with.  In my next post, I will further explore this relationship, in using more detailed
approaches with more specific functions of word seer, and perhaps even other tools that my new group members specialize in, in narrowing down my search more successfully to act five alone. However, this being said, no one is a complete expert, and one of the fundamental values in research is to adapt and learn as one progresses, and that is what I intend to do.

Narrowing the Scope: Zeroing in on Word Seer and the Digital Humanities

Dane Thibeault

Phase 1 Blog Post 2: Narrowing the Scope: Zeroing in on Word Seer and the Digital Humanities

I am writing this post to address some reassessments that I have made to my opinion of word seer, while additionally describing what role I had to play in the team project process to date. I am one apt to revoke my opinions of something if I find a cause for concern, and in regards to some of the functions of word seer, I experienced a few less than praise worthy difficulties during my research, which I will go into in detail throughout the duration of this recollection, while offering some insights on my assistance towards my team’s efforts.

Throughout the course of my team’s research in exploring the functions of the tool word seer, I have contributed a great deal to the overall process in individually assessing the tool’s potential to return relevant and insightful results from simply inputting data. In my previous blog post, and during my overall involvement process, I posed this fundamental question to myself: To what extent is word seer interesting, and to what extent is word seer insightful? What I mean by “interesting” is that many aspects of the tool may prove visually appealing or intriguing(Such as the feature depicted in the image below—yes, it is interesting to look at, but what does it really tell us about Hamlet?), yet, what I search for is the
more “insightful” qualities of the tool, such as what it can tell us that we could not readily or as easily identify through traditional text analysis, and how it is effective within the broader spectrum of the English discipline, altogether.

How I went about this process, the preliminary stages having been discussed in my previous blog post, evaluating to a lesser extent the same fundamental issue, was by exploring the capacity of the image comparative functions available in word seer to accurately represent trends or patterns that reveal details about the text of Hamlet, and the narrower study of act three scene four in particular, in a way that is either absent or otherwise complicated by traditional critical text analysis and closed reading. I concluded my last blog post with aspirations to further assess the word tree feature in particular, yet, I have concluded since then in my individual research, and as part of my contribution to the collaborative effort of the project, that this function is largely aesthetic and quantitative, and while it suggests word frequencies, it does little to suggest new avenues of research and interpretation regarding the text.

Therefore, seeing as to this disillusionment I experienced in my individual testing of the word tree function, I was further prompted to explore the more fundamental aspects of word seer, the words “described as” feature. What I was both surprised and disappointed to uncover, in a search of Claudius described as “blank”, was that both incoherent and unexpected results surfaced (pictured below, and keep this question in mind—does this sound like the villainous Claudius?) contributing to a mounting scepticism on my behalf.  As a result of this development, I felt compelled to shift my individual efforts and research more towards considering the overall impact of the tool, from the broader perspective of its impacts on the digital humanities, as opposed to its individual features, which I consider to be obscure and highly perplexing when I am working with them on my own. What on earth is a “snippet”, and how does one create of these, anyhow?

So, what is the overall significance of the word seer tool, which I initially felt to be its image qualities? My answer: I have no idea as of yet. In disarming myself of the ammunition that this tool is one of the rare few that can achieve qualitative value in hinting at the aspects of theme within a text, I was left with little to move on. However, I was able to reassess my priorities, and refocus my efforts. So how have I really individually contributed to the group work process, then? Simple: I started doing what I do best. What is that you ask? I simply grabbed a blank sheet of paper and a pen, and began to draft an outline, answering questions that I began to pose for myself, such as “why use word seer instead of other tools?” and “how could what I am trying to do with word seer be resolved better by either using other digital humanities tools or traditional text analysis?” and soon found that I was less overwhelmed about the whole process. I proceeded to complete my outline, jotting down some of the problems I faced, the lingering questions I had, and points that I felt would be effective to include in the presentation for the project, and promptly brought the outline with me to today’s group meeting to share with my team members. They were actually impressed, and were intrigued by many of the questions I raised, which has led me to conclude that there is a place for tradition in the rapidly advancing field of digital humanities, and additionally caused me to consider this underlying question: to what extent is there a potential to integrate traditional critical text analysis approaches, and the digital humanities? This is a question I have yet to provide an answer for, yet, I am determined to do so as my next ambition.

What ever happened to you, old friend?

Birth of a Salesman: How Word Seer and its Supplemented Images May Sell Us New Interpretations

     Dane Thibeault

English 265 Phase 1 Blog Post 1

   In being tasked with studying act III scene iv of Shakespeare’s Hamlet using the tool word seer, I was prompted to inquire more
about the tool itself, and to convey the results as the basis of this recollection.  However, a question I asked myself, prior to exploring the functions of word seer, was whether I believed it to be a simply interesting device, or an actually insightful device. What I mean by this is that I felt it necessary to deem whether or not the tool would return simply quantitative results with little meaning out of context, or rather, whether the device would return results that could be implemented in forming a qualitative conclusion, one that may not be easily reached from simple traditional close reading and text analysis.  My answer: quantitative results can form qualitative features, in identifying frequent words that may be used in establishing themes of studied texts, and word seer is an excellent tool in doing just so, through its visual functions.

     What are word seer’s limitations? That which we all possess: human intellect. How these problems may be overcome will largely be the target of my research. What I mean by this is that, while data figures may prove useful, they are not interpretations on their own, which can only be achieved by thoughtful evaluation. However, this brings me back to how many of the functions of word seer are a step in this direction. This being said. the more specific limitations of this tool I have yet to discover, and will attempt to uncover in further discovering how it works.

     The initial appeal of word seer, one that I feel deems it as more useful than a series of other digital tools, is that it is equipped with a heat map function, which allows for it to display the frequency of certain inputted words as they appear throughout a text, a visual feature that allows for comparisons and contrasts to be established.  For instance, a constantly recurring word can be inferred to represent a central theme within a text, as a word such as “lust”—one carrying thematic implications—may recur in one of Shakespeare’s other texts, such as Othello. Therefore, to test the validity of this feature, I inserted the word, “revenge” in the context of Hamlet, and was somewhat astounded by the results, (featured below) as they were characterized by a surprising lack of frequency of the word, contrary to my expectations, demonstrating how data features may be used to either verify or discredit superficial suppositions.

I was also surprised to discover that other words characteristic of Shakespeare’s works, excluding “love” and “death”, such as “chaste” “debt” and “honour” were remarkably less frequent than I would have previously anticipated based on my avid reading of the Bard’s other works(this test is featured below). This phenomenon may be used as evidence to suggest that Hamlet may differ greatly from the other texts in the Shakespearean corpus: an intriguing avenue for further research. Such questions as these may not only be tested with tools like word seer, but also, may be prompted by unexpected data results that are returned from such devices.

Therefore, it is now evident to me the profound impact of images on research. While one could repeatedly read Hamlet for analysis, it is unlikely that they could reach such observations so quickly and efficiently, and the further questions prompted by viewing an image would likely be absent from the process of inquisition.  Ammunition to support the significance of images to the process of research and interpretation, and the formulation of new theories and observations, is offered by  Martyn Jessop, in the following  article blurb:

So what to make of all of this, then? Essentially, what I wish to offer is an alternative approach to acquiring information about the themes of commonly studied texts. Therefore, word seer is an effective implement, as it allowed me to conclude, through preliminary trials, some potential ominous themes to characterize the text of Hamlet, through the words frequently used, such as how the repeated use of the word “death” has become an iconic thematic assumption of the play.  Further, this being said, what I desire to advocate is that word seer is made effective by its heat map image qualities, for comparison, contrast, visualization and frequency,  and that the further aim of my research is to continue to inquire into its other potential uses, to further determine its qualitative, insightful potential. Therefore, my next order of business is to explore other such features, such as the word tree below.