Fear and Loathing on Twitter: Exploring Negative Rhetoric in Tweets During the 2018 Midterm Election

This chapter contributes to research on the strategic use of emotions in political campaigns by gauging the presence of negative rhetoric in the social media posts of congressional candidates. Leveraging a dataset of tweets posted by candidates for the U.S. House during the last two months of the 2018 midterm election, we utilize a dictionary-based automated text analysis program to estimate the amount of negative language used by the candidates. Our results demonstrate that the campaign context can affect the likelihood that candidates use negative rhetoric in their tweets, as does gender and partisanship. Challengers, those in competitive races, losers, women, and Democrats were more likely to use anxious, sad, and angry words in their tweets during the run-up to Election Day 2018.