Measuring the Rise and Fall of a Subreddit using Text Analytics: The Life Course of r/Antiwork

The subreddit r/Antiwork first attracted significant public attention during the Great Resignation of 2021, when millions of workers in the United States quit their jobs in response to psychological distress and the economic downturn arising from the COVID-19 pandemic. At the peak of its momentum, in January 2022, an r/Antiwork moderator was interviewed by a Fox News reporter who, caricaturing the moderator as emblematic of the r/Antiwork community, dismissed both as lazy, entitled, and misguided. The interview became a watershed moment for the community, instigating an influx of targeted attacks on r/Antiwork and the moderator herself, and calling attention to the issue of representation of an intentionally leaderless community with ideologically disparate members. In this paper, we aim to quantitatively capture the effects of the Fox News interview on the r/Antiwork community through examining posts contributed to the subreddit from 2020-2022. To do so, we analyze the metadata of the posts – including metrics for each post such as the number of comments received, the username of the author, and the date of publication – along with conducting a sentiment analysis over time, thereby aiming to identify observable metrics in r/Antiwork that signal changes in community dynamics. Although our quantitative results demonstrate stability in post metrics related to a thriving community, content analysis suggests these metrics are unsound and merit further qualitative scrutiny. Specifically, we argue, the forms of quantitative information available present a misleading picture of community dynamics when member perceptions suggest otherwise.