Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent
Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent
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DOI：
10.1016/j.cognition.2022.105098
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发表时间：
2022-03-26
期刊：
影响因子：
3.4
通讯作者：
Dayan, P.
中科院分区：
文献类型：
--
作者：
Barnby, J. M.;Raihani, N.;Dayan, P.
为了从社交互动中受益，人们需要预测他们的社交伙伴的行为方式。这种预测是通过将先验期望与观察证据相结合而产生的，但先验从何而来以及它们是否影响对社会伙伴的信念的整合尚不清楚。此外，这个过程可能会受到偏执等因素的影响，在偏执中，对他人形成偏见印象的倾向很常见。我们在大型在线样本（n = 697）中使用修改后的社会价值取向（SVO）任务，表明参与者使用贝叶斯推理过程来了解合作伙伴，并根据自己的偏好确定先验信息。偏执狂与收入高于伴侣的偏好以及对伴侣社会偏好不太灵活的信念有关。参与者及其伴侣的偏好之间的一致性与更好的预测和减少对伴侣的有害意图有关。我们的数据和模型共同扩展了人际关系理论，展示了二元相似性如何通过产生更准确的预测和更少的威胁性印象来机械地影响社交互动。
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.