Twitter

We test whether candidates move to the extremes before a primary but then return to the center for the general election to appeal to the different preferences of each electorate. Incumbents are now more vulnerable to primary challenges than ever as social media offers a viable pathway for fundraising and messaging to challengers, while homogeneity of districts has reduced general election competitiveness. To assess candidates' ideological trajectories, we estimate the revealed ideology of 2020 congressional candidates (incumbents, their primary challengers, and open seat candidates) before and after their primaries, using a homophily-based measure of domains shared on Twitter. This method provides temporally granular data to observe changes in communication within a single election campaign cycle. We find that incumbents did move towards extremes for their primaries and back towards the center for the general election, but only when threatened by a well-funded primary challenge, though non-incumbents did not.

There is abundant anecdotal evidence that nondemocratic regimes are harnessing new digital technologies known as social media bots to facilitate policy goals. However, few previous attempts have been made to systematically analyze the use of bots that are aimed at a domestic audience in autocratic regimes. We develop two alternative theoretical frameworks for predicting the use of pro-regime bots: one which focuses on bot deployment in response to offline protest and the other in response to online protest. We then test the empirical implications of these frameworks with an original collection of Twitter data generated by Russian pro-government bots. We find that the online opposition activities produce stronger reactions from bots than offline protests. Our results provide a lower bound on the effects of bots on the Russian Twittersphere and highlight the importance of bot detection for the study of political communication on social media in nondemocratic regimes.