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  • Perspective
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A levels-of-analysis framework for studying social emotions

Nature Reviews Psychology volume 3, pages 198–213 (2024)Cite this article

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Abstract

Social emotions such as guilt and gratitude serve adaptive functions critical to social interactions and relationships. Therefore, an ecologically valid approach to studying the psychological and neural mechanisms of social emotions is to elicit and measure them in social interactive contexts, where relevant adaptive goals and functions are salient. However, multiple psychological and neurocognitive processes might be simultaneously activated during real-time social interactions: traditional observation-based tasks and self-report measures alone are not sufficient to capture and dissociate these processes. In this Perspective, we draw on Marr’s levels-of-analysis framework to argue that a holistic consideration of the goals and functions of a social emotion (computation level), formal modelling of its underlying cognitive operations (algorithm level), and neuroscientific measures of the biological bases of these cognitive operations (implementation level) will afford the theoretical frameworks and methodological tools necessary to advance understanding of social emotions. To support this argument, we describe research that showcases the utility of creative combinations of interactive tasks, neural and behavioural measures, and computational modelling for advancing understanding of how social emotions arise and achieve their adaptive goals and functions.

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Fig. 1: Studying social emotions in the levels-of-analysis framework.
Fig. 2: Approach and avoidance motivations following interpersonal transgression.
Fig. 3: Motivations underlying mixed social emotions in help recipients.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (grant 71942001 to X.Z., X.G., and Y.H.; grant 32371094 to X.G.; grant 31630034 to X.Z. and X.G.; grant 32200853 to Y.H.), by the Young Elite Scientists Sponsorship Program by China Association for Science and Technology (grants YESS20210176 and 2021QNRC001 to X.G.), the STI 2023 — Major Projects (grant 2021ZD0200500 to X.G., Y.H. and X.Z.), the Research Project of Shanghai Science and Technology Commission (grant 20dz2260300 to X.G. and X.Z.), and the Fundamental Research Funds for the Central Universities (to X.G. and X.Z.). Y.H. was supported by the Natural Science Foundation of Shanghai (grant 23ZR1418400) and by the Fundamental Research Funds for the Central Universities (2022ECNU-XWK-XK003). The authors thank D. Sznycer, R. Carlson and S. Wang for their constructive comments on the content and structure of the manuscript.

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  1. Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, CA, USA

    Hongbo Yu

  2. Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China

    Xiaoxue Gao, Yang Hu & Xiaolin Zhou

  3. Neuroscience Institute, New York University School of Medicine, New York, NY, USA

    Bo Shen

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Yu, H., Gao, X., Shen, B. et al. A levels-of-analysis framework for studying social emotions. Nat Rev Psychol 3, 198–213 (2024). https://doi.org/10.1038/s44159-024-00285-1

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