Abstract
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.
Highlights
Social information guides decision making across a broad range of animal taxa [1,2,3]
We develop a modelling framework that extends these insights to situations with multiple social sources, accommodating both simple heuristics, and more complex strategies
To investigate potential cognitive mechanisms underlying individuals’ integration of disparate social information, we developed a set of models unifying simple heuristics and more complex strategies
Summary
Social information guides decision making across a broad range of animal taxa [1,2,3]. Social information use often involves changing one’s mind after observing the behaviour of other individuals [20,21,22,23] This process is commonly investigated using estimation tasks in which people are allowed to revise their initial estimates after observing the estimate of a peer We use our model to predict how the observed adjustment strategies may shape belief dynamics in exemplary social environments that vary in the like-mindedness of peers (e.g. due to the social network structure). These simulations reveal how and when people’s prioritising of confirmatory social information can exacerbate filter bubble effects. They illustrate how individual differences in confir- 2 mation-based weighting can render beliefs to become more moderate (fostering group consensus) or more extreme (fuelling group polarization)
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