Emergence of Collective Accuracy in Socially Connected Networks

Dan Braha; Marcus A. M. de Aguiar

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arXiv · 2411.08625

Emergence of Collective Accuracy in Socially Connected Networks

Dan Braha·Marcus A. M. de Aguiar

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Abstract

We analyze the accuracy of collective decision-making in socially connected populations, where agents update binary choices through local interactions on a network. Each agent receives a private signal that is biased -- even marginally -- toward the correct alternative, and social influence mediates the aggregation of these signals. We show analytically that, in the large-population limit, the probability of a correct majority converges to a nontrivial expression involving the regularized incomplete beta function. Remarkably, this collective accuracy surpasses that of any individual agent whenever private signals are better than random, revealing that network-mediated influence can enhance, rather than impair, group performance. Our findings may inform the design of resilient decision-making systems in social, biological, and engineered networks, where accuracy must emerge from interdependent and noisy agents.

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Dan Braha, Marcus A. M. de Aguiar. 2024-11-13. Emergence of Collective Accuracy in Socially Connected Networks. https://arxiv.org/abs/2411.08625

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