For my CHI project, I am conducting a text analysis of a popular subreddit in which participants “snark” on fundamentalist Christian media to explore how community members recognize and respond to misogyny in fundamentalist media.
Reddit is a forum-based social media platform frequently used for geek, meme, and niche interest discussions, including extremist political and violently misogynist content, that also hosts a number of snark forums, subreddits dedicated to humorous mockery of television and internet stars. These snark subreddits are not known for their feminist discourse and often rely on misogyny, racism, and homophobia for their humor. However, in 2020, a series of intra-community ethical schisms erupted in a subreddit snarking on Christian fundamentalists. Some users were uncomfortable with snark that replicated the misogyny, homophobia, and racism for which users ostensibly mocked fundamentalists and expressed discomfort with an authoritarian moderation style that forced users to write increasingly vitriolic comments to avoid being banned from the subreddit. A new subreddit, the subject of this project, was created in response to the schism and has since cultivated ongoing discussions on the ethics of snarking, the overlap of snark and fundamentalist beliefs, and the role of snark in deprogramming from fundamentalist beliefs in ways that are uncommon on Reddit’s platform and in snark communities generally. The new subreddit has attempted to engage in deliberately feminist snark. Using computational topic modeling, I propose an analysis of how this community’s discourse has evolved over its first year, couched within an interactive narrative that invites visitors to the project to reflect on their own responses to misogyny, both fundamentalist- and snarker-generated.
In this project, I’m excited to expand my text analysis skills through computational topic modeling, but I also look forward to experimenting with a narrative-driven user experience and perhaps new, interactive ways of representing the results of my analysis that mirror the story-centric practices of the subreddit in question.