Knowledge of information cascades through social networks facilitates strategic gossip

Alice Xia, Yi Yang Teoh, Matthew R. Nassar, Apoorva Bhandari and Oriel FeldmanHall ()
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Alice Xia: Brown University
Yi Yang Teoh: Brown University
Matthew R. Nassar: Brown University
Apoorva Bhandari: Brown University
Oriel FeldmanHall: Brown University

Nature Human Behaviour, 2025, vol. 9, issue 10, 2169-2182

Abstract: Abstract Social networks are composed of many ties among many individuals. These ties enable the spread of information through a network, including gossip, which comprises a sizeable share of daily conversation. Given the number of possible connections between people in even the smallest networks, a formidable challenge is how to strategically gossip—to disseminate information as widely as possible without the target of the gossip finding out. Here we find that people achieve this goal by leveraging knowledge about topological properties, specifically, social distance and popularity, using a gossip-sharing task in artificial social networks (experiments 1–3, N = 568). We find a similar pattern of behaviour in a real-world social network (experiment 4, N = 187), revealing the power of these topological properties in predicting information flow, even in much noisier, complex environments. Computational modelling suggests that these adaptive social behaviours rely on mental representations of information cascades through the social network.

Date: 2025
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DOI: 10.1038/s41562-025-02241-2

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