Abstract
People need to accurately understand and predict others' emotions in order to build and maintain meaningful social connections. However, when they encounter new social partners, people often do not have enough information about them to make accurate inferences. Rather, they often resort to an egocentric heuristic, and make predictions about a target by using their own self-knowledge as a proxy. Is this egocentric heuristic a form of cognitive bias, or is it a rational strategy for real-world social prediction? If egocentrism provides a rational and effective solution to the challenging task of social prediction in naturalistic contexts, we should expect that a) egocentric predictions tend to be more accurate, and b) people rely on self-knowledge to a greater extent when it's more likely to be a good proxy. Using an emotion prediction task and personality measures, we assessed similarity and predictive accuracy between first-year college students and their new acquaintance roommate. Results demonstrated that, when people need to predict an unfamiliar target's emotions, self-knowledge can often effectively approximate knowledge about others, and thus support accurate predictions. Moreover, participants that were typical of the sample, whose self-knowledge can better approximate information about the target, relied more on self-knowledge in their predictions, and thus achieved higher accuracy. These findings suggest that people rationally tune their use of egocentrism based on whether it is likely to pay off. Overall, these findings demonstrate a rational side to a cognitive phenomenon usually framed as a cognitive pitfall, namely egocentric projection, when its natural decision context is taken into consideration.
Original language | English |
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Article number | 104521 |
Journal | Journal of Experimental Social Psychology |
Volume | 109 |
DOIs | |
State | Published - Nov 2023 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2023 Elsevier Inc.
Funding
The authors thank Judith Mildner, Mark Thornton, Casey Lew-Williams, Alin Coman, and Tom Griffiths for their advice on previous versions of the manuscript. This work was supported by National Institute of Mental Health (NIMH) grant R01MH114904 to D.I.T, and by European Union Horizon-2020 Marie Sklodowska-Curie Grant 101023860 to H·S.
Funders | Funder number |
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European Union Horizon-2020 | 101023860 |
National Institute of Mental Health | R01MH114904 |
Keywords
- Emotion prediction
- Emotions
- Interpersonal relationship
- Psychology
- Social cognition
- Social prediction
- Social psychology