Department of Psychology, Royal Holloway, University of London, London, UK; Cultural and Social Neuroscience Group, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Experimental Psychology, University College London, London, UK.
Cognition. 2022 Aug;225:105098. doi: 10.1016/j.cognition.2022.105098. Epub 2022 Mar 26.
To benefit from social interactions, people need to predict how their social partners will behave. Such predictions arise through integrating prior expectations with evidence from observations, but where the priors come from and whether they influence the integration into beliefs about a social partner is not clear. Furthermore, this process can be affected by factors such as paranoia, in which the tendency to form biased impressions of others is common. Using a modified social value orientation (SVO) task in a large online sample (n = 697), we showed that participants used a Bayesian inference process to learn about partners, with priors that were based on their own preferences. Paranoia was associated with preferences for earning more than a partner and less flexible beliefs regarding a partner's social preferences. Alignment between the preferences of participants and their partners was associated with better predictions and with reduced attributions of harmful intent to partners. Together, our data and model expand upon theories of interpersonal relationships by demonstrating how dyadic similarity mechanistically influences social interaction by generating more accurate predictions and less threatening impressions.
为了从社交互动中受益，人们需要预测他们的社交伙伴将如何表现。这种预测是通过将先前的期望与观察到的证据相结合来产生的，但先前的期望来自何处，以及它们是否会影响到对社交伙伴的信念的整合，目前还不清楚。此外，这个过程可能会受到偏执等因素的影响，在偏执中，对他人形成有偏见的印象的倾向是很常见的。我们在一个大型在线样本（n=697）中使用了改良的社会价值取向（SVO）任务，结果表明，参与者使用贝叶斯推理过程来了解合作伙伴，他们的先验基于自己的偏好。偏执与比伙伴赚更多钱的偏好以及对伙伴的社会偏好更缺乏灵活性的信念有关。参与者的偏好与其伙伴之间的一致性与更好的预测以及对伙伴的恶意意图的归因减少有关。总之，我们的数据和模型通过展示对偶相似性如何通过生成更准确的预测和更少威胁的印象来影响社交互动，从而扩展了人际关系理论。
