Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany.
Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
Proc Biol Sci. 2020 Nov 25;287(1939):20202413. doi: 10.1098/rspb.2020.2413.
Social information use is widespread in the animal kingdom, helping individuals rapidly acquire useful knowledge and adjust to novel circumstances. In humans, the highly interconnected world provides ample opportunities to benefit from social information but also requires navigating complex social environments with people holding disparate or conflicting views. It is, however, still largely unclear how people integrate information from multiple social sources that (dis)agree with them, and among each other. We address this issue in three steps. First, we present a judgement task in which participants could adjust their judgements after observing the judgements of three peers. We experimentally varied the distribution of this social information, systematically manipulating its variance (extent of agreement among peers) and its skewness (peer judgements clustering either near or far from the participant's judgement). As expected, higher variance among peers reduced their impact on behaviour. Importantly, observing a single peer confirming a participant's own judgement markedly decreased the influence of other-more distant-peers. Second, we develop a framework for modelling the cognitive processes underlying the integration of disparate social information, combining Bayesian updating with simple heuristics. Our model accurately accounts for observed adjustment strategies and reveals that people particularly heed social information that confirms personal judgements. Moreover, the model exposes strong inter-individual differences in strategy use. Third, using simulations, we explore the possible implications of the observed strategies for belief updating. These simulations show how confirmation-based weighting can hamper the influence of disparate social information, exacerbate filter bubble effects and deepen group polarization. Overall, our results clarify what aspects of the social environment are, and are not, conducive to changing people's minds.
社会信息的使用在动物王国中非常普遍，它可以帮助个体快速获取有用的知识并适应新的环境。在人类中，高度互联的世界提供了丰富的机会，可以从社会信息中受益，但也需要在与具有不同或冲突观点的人相处时应对复杂的社会环境。然而，人们如何整合来自多个与自己（不一致）或相互之间的社会信息源的信息，仍然在很大程度上不清楚。我们通过三个步骤来解决这个问题。首先，我们提出了一个判断任务，在这个任务中，参与者可以在观察三个同伴的判断后调整自己的判断。我们通过实验改变了社会信息的分布，系统地操纵了信息的方差（同伴之间的意见一致程度）和偏度（同伴的判断聚集在参与者判断的附近或远离）。正如预期的那样，同伴之间的方差越高，他们对行为的影响就越小。重要的是，观察一个单一的同伴确认参与者自己的判断，会显著降低其他（更远的）同伴的影响。其次，我们开发了一个框架，用于建模整合不同社会信息的认知过程，将贝叶斯更新与简单的启发式方法相结合。我们的模型准确地解释了观察到的调整策略，并揭示了人们特别关注与个人判断一致的社会信息。此外，该模型还揭示了个体之间在策略使用方面的强烈差异。第三，我们使用模拟探索了观察到的策略对信念更新的可能影响。这些模拟表明，基于确认的加权如何会阻碍不同社会信息的影响，加剧过滤气泡效应，并加深群体极化。总的来说，我们的研究结果阐明了哪些社会环境方面有利于改变人们的想法，哪些方面不利于改变人们的想法。
