Doctor of Philosophy (PhD)
Faculty of Science
Dr. Anne Wilson
While actual polarization is on the rise in the United States, perceived polarization (i.e., false polarization) is growing at an even faster rate, contributing to increased cross-party hostility. A meaningful amount of out-party dislike may be produced by partisans’ dramatic overestimates of the prevalence of extreme, undesirable views among political opponents. In the current research, we examine whether exposing people to out-party dissenters who challenge their copartisans’ extreme views might help reduce people’s misperceptions of their opponents’ extreme views, and possibly mitigate animosity. Across five studies (N = 3789), we explore how seeing public ingroup dissent (in the form of responses to an extreme tweet) changes the (mis)perceived prevalence of the extreme attitude amongst the opponent group. For both liberals and conservatives, seeing an interaction wherein a single political opponent disagreed with a (presumed) widely held extreme tweet lowered their estimates of how prevalent that attitude was, compared to seeing the tweet alone (Studies 1 and 2). This effect was strengthened when participants saw a “dogpile” of dissent, where multiple out-party members dissented against the extreme out-party tweet, compared to a single response, or no response at all (Studies 3, 4, & 5). The dissent condition did not directly affect feelings towards opponents, or willingness to engage with them. However, a serial mediation model revealed that exposure to dissent indirectly affected willingness to engage by reducing prevalence (over)estimates and, in turn, liking. Specifically, participants who saw opponent dissent lowered their estimates of opponent agreement with the extreme tweet; lower estimates were related to more positive feelings towards opponents, and more positive feelings were subsequently related to greater willingness to engage across the aisle.
Parker, Victoria, "The Power of Dissent: Mitigating False Polarization and Cross-Party Dislike in Online Interactions" (2023). Theses and Dissertations (Comprehensive). 2561.