2021/05/11 by Dekai Zhang, Zhang, D. Kai, Alexander Carver +1
Decision Sciences · Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #Game Theory and Applications #Opinion Dynamics and Social Influence #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2105.05072
openalex publication_date 2021/05/11 · openalex created_date 2021/05/24 · openalex updated_date 2026/07/28
We propose an agent-based network formation model under uncertainty with the objective of relaxing the common assumption of complete information, calling attention to the role beliefs may play in segregation. We demonstrate that our model is capable of generating a set of networks that encompasses those of a complete information model. Further, we show that by allowing agents to be biased toward each other based on observable attributes, our model is able to generate homophilous equilibria with preferences that are indifferent to these attributes. We accompany our theoretical results with a simulation-based investigation of the relationship between beliefs and segregation and show that biased beliefs are an important driver of segregation under incomplete information.