Digital Humanities

It is very difficult to argue for something when absolutes like the words “best” and “worst” are involved.  Is Yale the best college, are the Mets the worst baseball team?   Both of these answers are subjective and based much more heavily on opinion rather than fact.  Sure, there could be facts to support both claims, but undoubtably there are countless proven truths that can be used to argue against them as well.

That’s why when the question is popped asking whether or not using digital humanities technology is the best way to study literature, the answer has to be no.  While tools like the Wordle and Ngram are useful, they are relatively new, having only been created in the last decade.  Literature is an ancient art.  I’m sure you can make a Wordle using the text from the Bible, but I’m also sure that Matthew, Mark, Luke and John never did.

That being said, there simply has to be traditional, if not archaic, ways to study literature that are more effective than the digital humanities.  On one hand, it’s hard to believe that literature as a whole could survive for this long as a practice and a pastime if there were no effective way to discuss and analyze it before the digital humanities.  On the other, the digital humanities technologies simply have too many limitations to be the best way to study literature. Whatever the best way is, it is the best because it doesn’t have the holes or, frankly, the limitations that tools like Wordle and Ngram have.

The Wordle is a fine gadget.  Unique in it’s design and colorful in it’s end product,  it is a tool used to pinpoint which individual words in a certain text are used most predominantly.  The idea behind the Wordle is to break a large text down and transform it into a malay of individual words – arranged in all different shapes, sizes and orientations – in an attempt to create a display that would be able to convince even the most uninformed reader of the text‘s most and least important phrases.  In theory, it is the phrases that appear the largest in the Wordle that are the text’s main themes, or at least words that reflect these themes.  For example, in a Wordle created using the prose from Edgar Allen Poe’s short story The Gold-Bug, one of the most prominent words was “bug”, because of how often the word was used in the text.  The story is about a man who finds a special bug and how it changes his life.  Even someone who hadn’t read the short story could look at the Wordle (or the title for that matter) and know that whatever the plot may be, that there is definitely a bug involved.

The Wordle most glaring limitation stems from it’s lack of depth.  There is just not that much too it.  Sure, a display of a text’s most prominent words can give a reader insight to it’s plot, but even then, only to it’s outermost limits.  What a Wordle doesn’t do is dig into the meat of the plot.  Instead, it just kind of putters on the outer layers, giving us all it could, contently.

The Ngram is a distant relative of the Wordle.  While both are major members of the family that is the digital humanities, the two are very different – the Wordle examining the words of a certain text elusively, and the Ngram comparing certain words against various texts published over a period of time.  The Ngram is virtually the digital display of a comparative database-wide search whose targets and limits you set manually.  For example, the user of a Ngram enters words that are similar to each other in the search bar, and then specifies a time period in which the Ngram will search.  The Ngram then scrolls through years of literature and creates a line graph that accurately depicts the usage frequencies for each searched word.

An Ngram is most effective when related words are searched.  When words that go together are analyzed by an Ngram, one can see how the usage frequencies of different words evolve over time.  In a Ngram analysis of the insect theme prevalent in The Gold-Bug, various insect-related words were compared – “insect”, “bug”, “beetle”, “scarabeaus”, “spider” and “creepy-crawler” – and analyzed over a time range of 40 years before and after the text’s publication.

The results were interesting.  For whatever reason, the word “insect” was used in literature more frequently in the 1830s than it was in the 1820s or ‘40s, yet it then again saw a spike in usage after 1850.  All the other words were used in a relatively constant pattern over the forty years in question, and all were used less than “insect”.

What’s nice about the Ngram is that it allows a reader to dig into a level of literature not very often explored – that is, a historical one.  It is interesting because what the tool does is first break down the text to it’s simplest form (a single word), and then expand that word and compare it against an extremely broad spectrum of history.  Essentially constricting, expanding, analyzing and comparing the text all at the same time.

Like the Wordle, the Ngram does have limitations.  And these limitations ultimately lead to the digital humanities not being the best way to interpret literature.  The problem with the Ngram, simply, is that is while it analyzes specific words in the text, it doesn’t do much to inform a reader about the text itself.  It doesn’t even scrape the surface of many important literary elements like plot or characterization.  From a Ngram analysis sure we know how the text’s words stack up against the pages of history, but we don’t really know anything about how or why they’re important in their own story.

There is no denying that using the digital humanities is a unique way to study literature.  Various tools and gadgets in the field open up doors never before possible to a decipherer of text.  And for this reason they are fun, they are worthwhile and they are good.  But they are not the best.  They just can’t be, not with all the flaws they have.  The digital humanities technologies are so advanced and cutting edge that they tend to be terribly focused and specific, made exclusively to do a certain task.  And they do these tasks well.  However, it is this specificity that is their downfall.  In the world of literature, where so many bases are covered in so little time, and where there is so much to take in, a gadget with limited capabilities is of little use.  In order for a technology to be the absolute best way to study literature, it must cover all aspects of the literature in question.  Literature is a big, fat, juicy wedding cake, and that interpreter must go through all of the layers.





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