Spending the spring semester working on the TwitLit project was, for me, an engaging and hands-on first experience with the Digital Humanities (DH). As a research assistant, I worked with another student assistant, Meg Coyle, to document and record data on tweets in 2019 related to the writing community. Christian Howard-Sukhil, the head of the project and the DH Postdoctoral Fellow at the university, trained us to use Python scripts developed for scraping Twitter as well as Twarc tools developed through Documenting the Now (DocNow) in order to collect tweets (and accompanying metadata) that contained different writing-related hashtags. Using these scripts, we can record the number of tweets that contained a particular hashtag within a given time period, as well further information on each individual tweet, such as the timestamp or the number of likes and retweets.
From here, we are looking to expand the interpretation of this data into new avenues and to find ways to shed more light onto the sizable writing community on Twitter. For example, currently there are line graphs on the TwitLit website that display the growth of some of these hashtags, with analysis on what this data could mean. We have also speculated on ideas such as displaying viral tweets from the Twitter writing community on the website, in order to show what is drawing the most attention from inside and outside the community. One particularly exciting idea, which we unfortunately are unable to undertake without physically being at the university, is the geographic mapping of these tweets. It is possible to record the “geo-tag” of individual tweets, and through this we would be able to map where the writing community on Twitter comes from in the world, and further interpret this data and ask why tweets are concentrated in one place or another. Throughout the summer we plan to continue thinking of interesting ways to display the data we’ve collected and to keep the DH community at Bucknell updated through these blogs.