UC Riverside

A core principle of deliberative democracy posits that information exchange enhances the accuracy of group beliefs. However, in the face of unprecedented access to both first-hand empirical information and second-hand estimates from social networks, partisans often disagree on fundamental facts supported by data. In this dissertation, I integrate research on sampling models and motivated reasoning to examine the mechanisms driving partisan disagreements concerning gun control policies and their impact on the wisdom of partisan crowds. Across two studies, partisans learned about the impact of a policy increasing access to guns on subsequent crime rates, with manipulated access to first-hand empirical information, second-hand social estimates, or both. Our findings show that collective error reduces when individuals sample empirical data (Studies 1-2) and further decreases when they consider the average estimates of others (Study 1). The wisdom of crowds is also enhanced when partisans learn from viewing the estimates of fellow partisans, even when they have the choice to decide from which communities to sample (i.e., from Democrats or Republicans). However, collective accuracy was attenuated when partisans sampled social information due to biases in their sampling behavior (e.g., prioritizing in-group members) and the systematic bias of estimates along party lines (Study 2). These findings emphasize the importance of encouraging individuals to diversify their information sources and expand their social networks to include a wider range of perspectives. Furthermore, they reveal the boundary conditions of partisan social influence on the wisdom of crowds, indicating that while social influence can increase collective accuracy to a certain degree, it may also introduce systematic partisan biases that amplify divides, especially when social estimates propagate across networks and become increasingly detached from empirical evidence. In summary, this dissertation highlights the potential benefits and limitations of social influence in shaping collective judgments and offers valuable insights into how individuals gather information and update their beliefs. Ultimately, we hope this research can inform interventions aimed at fostering informed decision-making, bridging ideological divides, and paving the way for collaborative problem-solving in the face of persistent partisan motivations.