The Twin Impact of Homophily and Accessibility on Ideological Polarization
Document Type
Article
Digital Object Identifier (DOI)
10.1145/3145574.3145586
Conference Title
Proceedings of the 2017 International Conference of The Computational Social Science Society of the Americas
Publication Date
10-2017
Abstract
We present an agent-based model to explore the causes of one aspect of ideological polarization: the extent to which members of a society have social ties only with those they agree with. Specifically, we look at two variables that affect how an artificial social network structure is built: homophily, or the preference of individuals to form connections with others of the same "kind"; and accessibility, or the ease with which agents can form connections to others distant from it, as opposed to only local agents in its immediate vicinity. Our model builds a graph according to these two parameters, and then executes the classic Binary Voter Model (BVM) process on it whereby connected nodes influence one another's opinions. We find that counter to our original hypothesis, increasing the society's accessibility decreases its polarization, especially for high levels of homophily. Also, we discover that the rate at which agents form and dissolve friendships during the simulation plays a nuanced role in the way the society evolves.
Publisher Statement
© 2017 Copyright held by the owner/author(s).
ACM - "Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page."
Recommended Citation
Davies, Stephen. 2017. “The Twin Impact of Homophily and Accessibility on Ideological Polarization.” In Proceedings of the 2017 International Conference of The Computational Social Science Society of the Americas. Santa Fe, NM: ACM. https://doi.org/10.1145/3145574.3145586.
Comments
This article is freely accessible on the website of the Association of Computing Machinery (ACM) at: https://dl.acm.org/doi/10.1145/3145574.3145586.