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Cognitive Expectations of Homophily in Village Social Networks

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  • Feltham, Eric Martin

    (Columbia University)

  • Christakis, Nicholas

Abstract

Homophily, the tendency for individuals to associate with similar others, has long been treated as a central principle of social organization. Yet people may overestimate its importance in reasoning about their social networks. Here, we investigate individuals’ cognitive expectations of homophily and compare these expectations to actual homophily among 10,072 adults in 82 isolated Honduras villages. We elicited subjects’ beliefs about whether pairs of people in their village social networks were socially tied. We show that people deploy cognitive heuristics that substantially overestimate homophily, including based on wealth, ethnicity, gender, and religion. We also find that people exploit network structure when predicting ties between others, independent of expectations about homophily. Understanding cognitive homophily has implications for models of network formation, interventions targeting social behavior and information diffusion, and the maintenance of social inequality.

Suggested Citation

  • Feltham, Eric Martin & Christakis, Nicholas, 2026. "Cognitive Expectations of Homophily in Village Social Networks," SocArXiv z4nyq_v2, Center for Open Science.
  • Handle: RePEc:osf:socarx:z4nyq_v2
    DOI: 10.31219/osf.io/z4nyq_v2
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    References listed on IDEAS

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    1. Eric Feltham & Laura Forastiere & Nicholas A. Christakis, 2025. "Cognitive representations of social networks in isolated villages," Nature Human Behaviour, Nature, vol. 9(8), pages 1737-1753, August.
    2. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
    3. Bhargava, Palaash & Chen, Daniel L. & Sutter, Matthias & Terrier, Camille, 2022. "Homophily and Transmission of Behavioral Traits in Social Networks," IZA Discussion Papers 15840, IZA Network @ LISER.
    4. Richard Williams, 2012. "Using the margins command to estimate and interpret adjusted predictions and marginal effects," Stata Journal, StataCorp LLC, vol. 12(2), pages 308-331, June.
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