To Be or Not To Be a Romance

Whilst going over older materials I have stored, I came across an article by Witmore and Hope dealing with the Romances or Late Plays of Shakespeare.  It was a journal in Early Modern Tragicomedy (2007), the twenty-second installment of the “Studies in Renaissance Literature” series.   In it, Witmore and Hope write that John Fletcher’s “definition of genre not only specifies what must be in a play to qualify it for membership in a genre, but also what it must lack”.  Fletcher’s postulation of what must be present, but also not present, to belong to a genre is similar to what I tested in my last post by adding and removing the characters that plays were named after.  In review, it was a mixed bag of results leading towards both the idiolects of the play’s main characters and the texture of plays themselves as the primary reasons for clustering.  However Witmore and Hope’s article sparked a new thought process in my head.  Since readers and critics as far back in time as Fletcher have noted the peculiar differences between the Romances and the rest of Shakespeare’s corpus, does that mean by following Fletcher’s formula that adding or subtracting characters will affect a play’s genre classification?  One of Witmore’s earliest views from Docuscope was a simplified dendrogram noting a genre specific clustering result from an unbiased word tagging program.  I have since noticed particular genre related movement in the Romeo and Juliet post, but I am now trying to combine a three hundred year-old literary critic’s mind with a modern machine’s processes.  In sum, I wish to determine if the idiolects of the main characters assist the Romances in clustering differently from the rest of Shakespeare’s corpus and whether or not the isolation of these particular characters’ lines from the whole play reacts with the genre specific clustering already present.

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Romeo and Juliet without Romeo and Juliet

Like I mentioned previously, I began this project tired, under a time restraint, and with no idea of where it would lead me.  However, I had hope.  At a few research meetings previously, Bill Blake had mentioned doing some work with Docuscope in the sense of Hamlet without the Prince.  While I had never really seen the result of his work, the idea of a play without its main character or main characters enticed me.  It didn’t take me long to find my favorite play, Romeo and Juliet, and sit down at my computer.  Referencing my second edition of the Riverside Shakespeare, I cut and pasted lines spoken by each of the characters throughout the play until I had, technically, two different plays.  I retained the initial text file, split it up by Act again, and then created a new text file for the whole play, without any of Romeo or Juliet’s lines.  I also separated the Acts again, without their lines, and created two new files; one with all of Romeo’s lines and with Juliet’s.  The images I came up with are below.  The methods remained the same from the previous post: Hierarchical Cluster, Best Guess Analysis, Ward’s test, Colored Coded Dendrogram with a Distance Scale performed at a Cluster level analysis of Docuscope’s output.