Competition Between Homophily and Information Entropy Maximization in Social Networks

TL;DR

This paper explores the competing influences of homophily and information entropy maximization in social network formation, revealing how they shape local structures and the nature of social ties.

Contribution

It introduces a theoretical and experimental analysis of the competition between homophily and entropy maximization, highlighting their coexistence in social network evolution.

Findings

Homophily promotes local clustering and strong ties.

Entropy maximization encourages weak, long-range connections.

Both mechanisms coexist in social network development.

Abstract

In social networks, it is conventionally thought that two individuals with more overlapped friends tend to establish a new friendship, which could be stated as homophily breeding new connections. While the recent hypothesis of maximum information entropy is presented as the possible origin of effective navigation in small-world networks. We find there exists a competition between information entropy maximization and homophily in local structure through both theoretical and experimental analysis. This competition means that a newly built relationship between two individuals with more common friends would lead to less information entropy gain for them. We conjecture that in the evolution of the social network, both of the two assumptions coexist. The rule of maximum information entropy produces weak ties in the network, while the law of homophily makes the network highly clustered locally and the individuals would obtain strong and trust ties. Our findings shed light on the social network modeling from a new perspective.