New Digital Humanities projects are constantly serving to augment scholarship in new ways. Most DH projects share a common thread of extracting and amassing data from collections of texts (literary works, scholarly works, web data, etc.), however the true augmenting lies in the wide range of research that is done after the data is collected. This data can provide a model for examining more nebulous phenomena, such as emotion. In a study titled “Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter,” Sheridan Dodds and other researchers studied individual tweets based on frequency and significance of certain words to gain insight on hedonism and emotion. The study operates under the principle that “the raw word content of tweets does appear to reflect people’s current circumstances” (Dodds). In this sense, Twitter and other forms of social media serve as additional embodied human communication tools – rather than being separate entities from the humans who use them, these Twitter accounts are an auxiliary part of the human himself. With progress being made in DH, it is possible for humans to be identified by analysis of their auxiliary communication tools. In her article for National Geographic, Virginia Hughes describes how scholars were able to examine literary data to determine that the real identity of pseudonymous writer Robert Galbraith was in fact famed author J.K. Rowling. The idea that simply examining words and word patterns could point to a conclusion of “very characteristically Rowling” (Hughes) certainly finds itself somewhere on the “awesome-creepy” scale.
In her book How We Think, Hayles examines what can make this sort of literary data-extraction unsettling. She discusses the differences between human interpretation of literary material and “machine reading”, and notes that human egocentricity may lead to the principle that “human interpretation should be primary in analyzing how events originate and develop” (Hayles 29). Traditional humanities scholars often rush to discredit the digital humanities and techniques of machine reading or “distant reading,” but they often lose sight of the fact that DH seeks to augment existing scholarship rather than replace it. These sorts of scholars remind me of some of the “console cowboys” from Neuromancer, who see simstim as an inferior tool compared to jacking-in to cyberspace. Eventually, Case sees that simstim can be an extremely powerful tool to serve different purposes (Gibson). DH represents a model of scholarship that uses as many tools as possible to explore academic inquiries.
Citations:
Dodds PS, Harris KD, Kloumann IM, Bliss CA, Danforth CM (2011) Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter. PLoS ONE 6(12): e26752. doi:10.1371/journal.pone.0026752
Gibson, William. Neuromancer. New York: Ace, 1984. Print.
Hayles, Katherine. How We Think: Digital Media and Contemporary Technogenesis. Chicago: U of Chicago, 2012. Print.
Hughes, Virginia. “How Forensic Linguistics Outed J.K. Rowling (Not to Mention James Madison, Barack Obama, and the Rest of Us).” Phenomena. National Geographic, 19 July 2013. Web. 11 Sept. 2014.
