UC Davis

While the online sphere is believed to expose individuals to a wider array of viewpoints, a worry about self-reinforcing political echo chambers also persists. We join this scholarly debate by focusing on individual motives for political discussion and dyadic- and structural-level mechanisms that can drive one’s message-selection decision in online discussion settings. Using unobtrusively logged behavioral data matched with panel survey responses, our temporal exponential random graph model (TERGM) analysis indicates that message selection in online discussion settings is largely driven by the similarity of one’s candidate evaluative criteria and various endogenous structural factors, whereas the impact of overt partisan preference in shaping message selection is much more limited than is often assumed.