is our reward

Publications in Collective Motion by NOMIS researchers

NOMIS Researcher(s)

Published in

December 17, 2021

Competition for social influence is a major force shaping societies, from baboons guiding their troop in different directions, to politicians competing for voters, to influencers competing for attention on social media. Social influence is invariably a competitive exercise with multiple influencers competing for it. We study which strategy maximizes social influence under competition. Applying game theory to a scenario where two advisers compete for the attention of a client, we find that the rational solution for advisers is to communicate truthfully when favored by the client, but to lie when ignored. Across seven pre-registered studies, testing 802 participants, such a strategic adviser consistently outcompeted an honest adviser. Strategic dishonesty outperformed truth-telling in swaying individual voters, the majority vote in anonymously voting groups, and the consensus vote in communicating groups. Our findings help explain the success of political movements that thrive on disinformation, and vocal underdog politicians with no credible program.

Research field(s)
Health Sciences, Biomedical Research, Developmental Biology

In emergencies, social coordination is especially challenging. People connected with each other may respond better or worse to an uncertain danger than isolated individuals. We performed experiments involving a novel scenario simulating an unpredictable situation faced by a group in which 2480 subjects in 108 groups had to both communicate information and decide whether to ‘evacuate’. We manipulated the permissible sorts of interpersonal communication and varied group topology and size. Compared to groups of isolated individuals, we find that communication networks suppress necessary evacuations because of the spontaneous and diffuse emergence of false reassurance; yet, communication networks also restrain unnecessary evacuations in situations without disasters. At the individual level, subjects have thresholds for responding to social information that are sensitive to the negativity, but not the actual accuracy, of the signals being transmitted. Social networks can function poorly as pathways for inconvenient truths that people would rather ignore.

Research field(s)
Natural Sciences, Mathematics & Statistics, Applied Mathematics