Research Project

Twitter discourse has gained a more influential role in shaping public attitudes in the past few years. The platform continues to be known as a site of worsening polarization and heated culture wars that gives public figures a strong level of influence. Its largely written corpus form also means that it can be analyzed for linguistic features that indicate emotive or persuasive language. Prior research by Christopher Potts and Florian Schwarz has identified that increased use of the demonstratives this and that is correlated with strongly positive or negative online reviews, which is hypothesized to create emotional distance or proximity by involving the listener in a shared sentiment. Following the trend of sentiment analysis of linguistic corpora in NLP, I analyze language from twenty-eight of the most active U.S. representatives on the platform to measure whether their use of these demonstratives in posts immediately preceding the 2022 elections is higher than the average Twitter user’s during the same time period. I then evaluate responses from individuals surveyed about their emotional reactions to tweets with high and low frequency of demonstratives to measure the affective power of this and that. More research is needed to determine a correlation between affective demonstratives and polarization on Twitter, but my research applies existing linguistic trends to the corpus available on Twitter to measure real-world effects.