In recent years, literature has been getting attention from an unusual quarter: mathematics. Alongside statistical physicists analyzing the connections between characters in the Icelandic sagas, and computer scientists exploring the life and death of words in English fiction, a team of mathematicians at the University of Vermont have now looked at more than 1,000 texts to see if they could automatically extract their emotional arcs. And their results show something interesting, not just about narratives, but also about using this approach to study literature.
The Vermont researchers worked with test subjects to create a program capable of assigning emotional value—positive, negative or neutral—to words. ‘Terrorist’ is rated negative in the program’s word bank, while ‘win’ is positive. Then they selected texts from the massive volunteer effort to digitize books known as Project Gutenberg, which currently exists as a repository of public-domain writings. Finally, the researchers ran a series of analyses to chart the shape of the emotional arcs in the texts.
And indeed, according to the paper put up on ArXiv.org in June 2016, some patterns showed up again and again. About 85 percent of the works that the researchers looked at could be separated into six groups. Some of the groups lent themselves to colorful names—such as ‘Icarus,’ for an emotional type that rises, then falls; and ‘Rags to Riches,’ for one that starts negative and then rises. Some of Gutenberg’s most-downloaded works fit the ‘Cinderella’ model, with a rise, a fall, and a rise. You can see how you might start to draw conclusions about what stories play best, or how small the true number of arcs in human storytelling is.