Proceedings of the Annual Meeting of the Cognitive Science Society

People use incomplete social network information to infer relationships. For example, if two individuals have many mutual friends, people infer they are friends with each other. We examined whether these inferences depend on domain-specific knowledge about social relationships, or instead depend on domain general-reasoning about statistics and proportions. In two experiments, participants (N=526) either saw partial information about social networks, like friendships between people, or about non-social networks, like wired connections between electrical parts. They then judged if two entities in each network were directly connected to each other. The entities varied in the number of connections and the proportion of mutual connections. People made similar judgments across social and non-social networks: with greater proportion of mutual connections, the two entities were judged as more likely to be connected to each other. In sum, inferences about networks might primarily depend on reasoning about statistics and proportions.