Americans view their in-party members positively and out-party members negatively. It remains unclear, however, whether in-party affinity (i.e., positive partisanship) or out-party animosity (i.e., negative partisanship) more strongly influences political attitudes and behaviors. Unlike past work, which relies on survey self-reports or experimental designs among ordinary citizens, this pre-registered project examines actual social media expressions of an exhaustive list of American politicians as well as citizens' engagement with these posts. Relying on 1,195,844 tweets sent by 564 political elites (i.e., members of US House and Senate, Presidential and Vice-Presidential nominees from 2000 to 2020, and members of the Trump Cabinet) and machine learning to reliably classify the tone of the tweets, we show that elite expressions online are driven by positive partisanship more than negative partisanship. Although politicians post many tweets negative toward the out-party, they post more tweets positive toward their in-party. However, more ideologically extreme politicians and those in the opposition (i.e., the Democrats) are more negative toward the out-party than those ideologically moderate and whose party is in power. Furthermore, examining how Twitter users react to these posts, we find that negative partisanship plays a greater role in online engagement: users are more likely to like and share politicians' tweets negative toward the out-party than tweets positive toward the in-party. This project has important theoretical and democratic implications, and extends the use of trace data and computational methods in political behavior.
