Kurt Vonnegut once gave a lecture on storytelling, and explained that there were but six basic plots in literature. With this in mind, I found Matthew Jocker’s Sentiment Analysis R based program, Syuzhet. This program, using a clean, text only version of a work of literature, graphs sentiment values of a novel. The Syuzhet program uses its own lexicon of positive and negative words to create these graphs. Syuzhet has been around for quite a few years and has been updated many times to use context to ensure the most accurate graph is given for a novel. It is not infallible, but after running a few tests with the program I found it well suited for my needs, graphing a sarcastic novel correctly and highlighting the chapters with rising and falling action based only on sentiment.
This idea of the project has gone through a few evolutions as there have been quite a few set backs. Ultimately, my ideas on what literature to graph has changeg, and is still changing, based on availability of legal, public-use e-text. Originally, I wanted to graph the entire corpus of Kurt Vonnegut to prove his six plot theory within his own work. However finding any free text other than Cat’s Cradle and Slaughterhouse Five is impossible. I looked into scanning and OCR programs, but the too much time would be used to create my own e-text, edit the documents to ensure OCR recognized every character, and then format the text for analysis. After many variations, I decided to look into popular novels to compare their plot lines and success. I am still compiling this corpus as the e-text issue is impeding my progress, but once finalized my project will proceed quickly.
Ultimately, I want to utilize sentiment value technology to show trends in best selling or popular novels. Doing this would allow me to visualize and extrapolate a correlation between the two, which would open up an entirely new avenue of interpretation and understanding literature. However, this program and my project is one I plan to use for the foreseeable future as it has many outlets for research. One could look at the success of a certain sentiment plot type when examples of it were published and then map the success of the examples throughout major world events to see how history affects the success of that plot type. This type of sentiment analysis could also disprove theories that certain types of literature, romance for example, follow the same plot type every time.
Taken out of context a rose by any other name is a novel. If there are only 6 formulas for the novel it would open up entire new ways of comparison across genre and historical categories. It could also help deepen our understanding of the history of novels and their success through the ages. By graphing my corpus and comparing the graphs I will not only begin to bolster the six plot argument but also compare the most successful plot types for public consumption. (511)
Booker, Christopher. The Seven Basic Plots: Why We Tell Stories. Bloomsbury, 2016.
Jockers, Matthew. “Jocker’s Blog.” Matthew L. Jockers, 16 Dec. 2017, http://www.matthewjockers.net/.
Moretti, Franco. “Patterns and Interpretation.” Literary Lab Pamphlet, Sept. 2015, doi:ISSN 2164-1757.
Shultes, Allison. “How One Digital Humanist Visualized the Shapes of 50,000 Novels.” Storybench, Northeastern University School of Journalism, 27 Apr. 2017, http://www.storybench.org/how-one-digital-humanist-visualized-the-shapes-of-50000-novels/.
Vonnegut, Kurt, and Daniel Simon. A Man Without a Country. Seven Stories Press, 2005.
Vonnegut, Kurt. Wampeters, Foma & Granfalloons (Opinions). The Dial Press, a Division of Random House, 2006.