Abstract.
A prominent explanation for the proliferation of political misinformation and the growing belief polarization is that people engage in motivated reasoning to affirm their ideology and to protect their political identities. An alternative explanation is that people seek the truth but use partisanship as a heuristic to discern credible from dubious sources of political information. In two experiments, we test these competing explanations in a dynamic setting where Democrats and Republicans are repeatedly exposed to messages from ingroup or outgroup partisan sources and can gradually learn which source is credible based on external feedback. Both Democrats and Republicans initially incorporated information from ingroup sources more than from outgroup sources. This pattern was stronger among partisans that displayed high affective polarization. Across rounds, this partisan bias declined, or even changed direction, as supporters of both groups gradually incorporated information from reliable sources more than unreliable sources irrespective of the source’s partisanship. Importantly, the content of the shared information (i.e., neutral vs political) and the presence of partisan sources as opposed to neutral sources did not affect the learning process indicating the presence of strong accuracy motives. In contrast, increased uncertainty regarding source reliability undermined the learning process. These findings demonstrate that partisans follow Bayesian learning dynamics. Although they initially display a partisan bias in the incorporation of information, they overcome this bias in the presence of external feedback and learn to trust credible sources irrespective of partisanship.
