Model simulations for evolution of beliefs in two example settings. The y-axis represents the mean of the belief distribution, and the x-axis shows the number of observed debunking actions; debunking actions 0 represents the prior belief on each variable. Truth of the perspective varies between 0 and 1, with larger values representing a higher likelihood of truth. Accuracy varies between 0 and 1, with larger values representing a higher motivation to respond in proportion to the truthfulness of the claims-debunk likely false content and do nothing in response to likely true content. Bias varies between −0.5 and 0.5, with positive values representing bias in favor and negative values representing bias against the perspective-e.g. based on the political orientation of the perspective. The shaded ribbon shows the standard deviation of belief distribution. The solid line represents the subgroup who a priori believes the perspective of the claims is likely true (i.e. the proponent subgroup), and the dashed line represents the subgroup who a priori believes the perspective of the claims is likely false (i.e. the opponent subgroup). Left column: A setting in which the subgroups' prior differing beliefs about the topic are uncertain, and their shared prior beliefs about authority's legitimacy are confident-high accuracy and impartiality, leads to effective debunking of false content. Right column: A setting in which the subgroups' prior differing beliefs about the topic are confident and their shared prior beliefs about the authority's motivations are uncertain, leads to polarization of beliefs about the authority in addition to beliefs about the topic remaining polarized.

Model simulations for evolution of beliefs in two example settings. The y-axis represents the mean of the belief distribution, and the x-axis shows the number of observed debunking actions; debunking actions 0 represents the prior belief on each variable. Truth of the perspective varies between 0 and 1, with larger values representing a higher likelihood of truth. Accuracy varies between 0 and 1, with larger values representing a higher motivation to respond in proportion to the truthfulness of the claims-debunk likely false content and do nothing in response to likely true content. Bias varies between −0.5 and 0.5, with positive values representing bias in favor and negative values representing bias against the perspective-e.g. based on the political orientation of the perspective. The shaded ribbon shows the standard deviation of belief distribution. The solid line represents the subgroup who a priori believes the perspective of the claims is likely true (i.e. the proponent subgroup), and the dashed line represents the subgroup who a priori believes the perspective of the claims is likely false (i.e. the opponent subgroup). Left column: A setting in which the subgroups' prior differing beliefs about the topic are uncertain, and their shared prior beliefs about authority's legitimacy are confident-high accuracy and impartiality, leads to effective debunking of false content. Right column: A setting in which the subgroups' prior differing beliefs about the topic are confident and their shared prior beliefs about the authority's motivations are uncertain, leads to polarization of beliefs about the authority in addition to beliefs about the topic remaining polarized.

Source publication
Article
Full-text available
In polarized societies, divided subgroups of people have different perspectives on a range of topics. Aiming to reduce polarization, authorities may use debunking to lend support to one perspective over another. Debunking by authorities gives all observers shared information, which could reduce disagreement. In practice, however, debunking may have...

Contexts in source publication

Context 1
... demonstrate the evolution of beliefs in two contrasting example settings (Fig. 2). In the first example, both subgroups share priors that the authority's motives include a high motive for accuracy, no bias in favor or against the claims' perspective, and both subgroups are uncertain about their initial beliefs about the topic. In this situation, debunking is effective: after five debunking acts, the proponent ...
Context 2
... and the proponent group instead quickly came to believe that the authority was actually biased against the debunked perspective. If the groups initially suspected that the authority was biased against the debunked perspective, then debunking also failed regardless of certainty about the differing beliefs about the topic or the authority's bias (Fig. S2). Overall these simulations suggest that the effects of debunking on observers' beliefs could be enormously variable, depending sensitively on the value and uncertainty of prior beliefs about both the topic and the authority's motives (see also Figs. S3 and S4 for a larger set of ...
Context 3
... a mixture of decisions to debunk and decisions to say nothing about the truth of the claim, i.e. abstain. The same model developed here can be used to simulate the evolution of beliefs in these mixed situations. For example, Fig. S7 illustrates the effect of a single debunking (in round 3) and four abstentions using the same initial priors as Fig. 2. When observers have high confidence in either their views about the authority (left) or about the perspective's truth (right), choices to abstain from debunking do not affect these certain beliefs. However, when observers have higher levels of uncertainty, the confusion introduced by the mixed debunking causes beliefs to evolve ...
Context 4
... beliefs. However, when observers have higher levels of uncertainty, the confusion introduced by the mixed debunking causes beliefs to evolve nonmonotonically. Indeed, in the case where convergence occurs, the combination of four abstentions and one debunking yields convergence towards the debunked perspective, contrary to the pattern observed in Fig. 2. While fully evaluating the complexity introduced by mixed cases is outside the scope of this manuscript, the extreme case of one debunking action and four abstentions illustrates that the impact of failing to debunk all claims from a particular perspective can both undermine the opportunity to converge on true beliefs, and influence ...

Similar publications

Article
Full-text available
In the Post-Truth era, where people's personal values and thoughts are accepted as reality and there is no need to try to reach the truth by rational reasoning, people aim to produce, spread and have their own reality accepted by using the power of new media tools in line with their beliefs, emotions and sensitivities. Every news content produced i...

Citations

Article
This article provides an introduction to and overview of the articles in the PNAS Nexus Special Feature on Polarization and Trust.