No CrossRef data available.
Article contents
Coalitionary psychology and group dynamics on social media
Published online by Cambridge University Press: 07 July 2022
Abstract
Pietraszewski's model allows understanding group dynamics through the lens of evolved coalitionary psychology. This framework is particularly relevant to understanding group dynamics on social media platforms, where coalitions based on salience of group identity are prominent and generate unique frictions. We offer testable hypotheses derived from the model that may help to shed light on social media behavior.
- Type
- Open Peer Commentary
- Information
- Copyright
- Copyright © The Author(s), 2022. Published by Cambridge University Press
References
Barberá, P. (2020). Social media, echo chambers, and political polarization. In Persily, N., & Tucker, J. (Eds.), Social media and democracy: The state of the field (pp. 34–55). Cambridge University Press. https://doi.org/10.1017/9781108890960.CrossRefGoogle Scholar
Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205. https://doi.org/10.1509/jmr.10.0353.CrossRefGoogle Scholar
Blaine, T., & Boyer, P. (2018). Origins of sinister rumors: A preference for threat-related material in supply and demand of information. Evolution and Human Behavior, 39(1), 67–75 https://doi.org/10.1016/j.evolhumbehav.2017.10.001.CrossRefGoogle Scholar
Boyer, P., Firat, R., & van Leeuwen, F. (2015). Safety, threat, and stress in intergroup relations: A coalitional index model. Perspectives on Psychological Science 10(4), 434–450. https://doi.org/10.1177/1745691615583133.CrossRefGoogle ScholarPubMed
Brady, W. J., Wills, J. A., Burkart, D., Jost, J. T., & Van Bavel, J. J. (2019). An ideological asymmetry in the diffusion of moralized content on social media among political leaders. Journal of Experimental Psychology: General, 148(10), 1802–1813. https://doi.org/10.1037/xge0000532.CrossRefGoogle ScholarPubMed
Cinelli, M., Morales, F. G. D., Galeazzi, A., Quattrociocchi, W., & Starmini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9), e2023301118. https://www.doi.org/10.1073/pnas.2023301118.CrossRefGoogle ScholarPubMed
Dos Santos, M., & Rankin, D. J. (2010). The evolution of punishment through reputation. Proceedings of the Royal Society B: Biological Sciences 278, 371–377. https://doi.org/10.1098/rspb.2010.1275.CrossRefGoogle ScholarPubMed
Druckman, J. N., & Levendusky, M. S. (2019). What do we measure when we measure affective polarization? Public Opinion Quarterly, 83(1), 114–122. https://www.doi.org/10.1093/poq/nfz003.CrossRefGoogle Scholar
Hutchens, M. J., Hmielowski, J. D., & Beam, M. A. (2019). Reinforcing spirals of political discussion and affective polarization. Communication Monographs, 86, 357–376. https://www.doi.org/10.1080/03637751.2019.1575255.CrossRefGoogle Scholar
Iyengar, S., Lelkes, Y., Levendusky, M., Malhotra, N., & Westwood, S. J. (2019). The origins and consequences of affective polarization in the United States. Annual Review of Political Science, 22, 129–146. https://doi.org/10.1146/annurev-polisci-051117-073034.CrossRefGoogle Scholar
Iyengar, S., Sood, G., & Lelkes, Y. (2012). Affect, not ideology: A social identity perspective on polarization. Public Opinion Quarterly, 76, 405–431 https://www.doi.org/10.1093/POQ/NFS038.CrossRefGoogle Scholar
Karlsen, R., Steen-Johnsen, K., Wollebæk, D., & Enjolras, B. (2017). Echo chamber and trench warfare dynamics in online debates. European Journal of Communication, 33(3), 257–273. https://doi.org/10.1177/0267323117695734.CrossRefGoogle Scholar
Mishra, S., Barclay, P., & Sparks, A. (2017). The relative state model: Integrating need-based and ability-based pathways to risk-taking. Personality and Social Psychology Review, 21, 176–198.CrossRefGoogle ScholarPubMed
Nguyen, A., & Vu, H. T. (2019). Testing popular news discourse on the “echo chamber” effect: Does political polarisation occur among those relying on social media as their primary politics news source? First Monday, 24(6). https://doi.org/10.5210/fm.v24i6.9632.Google Scholar
Paluck, E., Green, S., & Green, D. (2019). The contact hypothesis re-evaluated. Behavioural Public Policy, 3(2), 129–158. https://www.doi.org/10.1017/bpp.2018.25.CrossRefGoogle Scholar
Petersen, M. B. (2015). Evolutionary political psychology. In Buss, D. M. (Ed.) The handbook of evolutionary psychology (2nd ed., pp. 1084–1102). Wiley.Google Scholar
Shore, J., Baek, J., & Dellarocas, C. (2018). Network structure and patterns of information diversity. MIS Quarterly, 42(3), 849–872. https://www.doi.org/10.25300/MISQ/2018/14558.CrossRefGoogle Scholar
Tooby, J., & Cosmides, L. (2010). Groups in mind: Coalitional psychology and the roots of war and morality. In Høgh-Olesen, H. (Ed.), Human morality and sociality: Evolutionary and comparative perspectives (pp. 191–234). Palgrave Macmillan.CrossRefGoogle Scholar
Target article
Toward a computational theory of social groups: A finite set of cognitive primitives for representing any and all social groups in the context of conflict
Related commentaries (29)
A neuroscientific perspective on the computational theory of social groups
Advantages and limitations of representing groups in terms of recursive utilities
Are we there yet? Every computational theory needs a few black boxes, including theories about groups
Beyond folk-sociology: Extending Pietraszewski's model to large-group dynamics
Can group representations based on relational cues warrant the rich inferences typically drawn from group membership?
Coalitionary psychology and group dynamics on social media
Compassion within conflict: Toward a computational theory of social groups informed by maternal brain physiology
Conciliation and meta-contrast are important for understanding how people assign group memberships during conflict situations
Developmental antecedents of representing “group” behavior: A commentary on Pietraszewski's theory of groups
Group? What group? A computational model of the group needs a psychology of “us” (not “them”)
How do we know who may replace each other in triadic conflict roles?
Interacting with others while reacting to the environment
Internal versus external group conflicts
Latent structure learning as an alternative computation for group inference
Learning agents that acquire representations of social groups
More than one way to skin a cat: Addressing the arbitration problem in developmental science
On vagueness and parochialism in psychological research on groups
Paranoia reveals the complexity in assigning individuals to groups on the basis of inferred intentions
Private versus public: A dual model for resource-constrained conflict representations
Psychological and actual group formation: Conflict is neither necessary nor sufficient
Shadow banning, astroturfing, catfishing, and other online conflicts where beliefs about group membership diverge
Shared intentionality and the representation of groups; or, how to build a socially adept robot
Signals and cues of social groups
Social groups and the computational conundrums of delays, proximity, and loyalty
Societies and other kinds of social groups
The labelled container: Conceptual development of social group representations
Towards a computational network theory of social groups
Triadic conflict “primitives” can be reduced to welfare trade-off ratios
Using laboratory intergroup conflict and riots as a “stress test”
Author response
More “us,” less “them”: An appeal for pluralism – and stand-alone computational theorizing – in our science of social groups