Quantifying opinion homophily in online social networks: A bounded confidence perspective

2026-04-25

AI Summary

This study addresses the quantification of opinion homophily in online social networks from a cognitive perspective, moving beyond conventional demographic analyses. Grounded in bounded confidence theory, it leverages heterogeneous data from Reddit and Twitter across three polarizing topics, constructing user opinion representations through sentiment analysis and fact-checking. The interaction network is modeled using follows (strong ties) and replies (weak ties). Findings reveal that users’ interaction neighborhoods in opinion space are significantly more concentrated than random expectations, with tolerance intervals often exhibiting asymmetry skewed toward local majority positions. The results demonstrate that both tie strength and issue polarization amplify opinion homophily, and that users display greater tolerance toward mainstream views, offering novel evidence for a bounded-confidence mechanism underlying value homophily in online environments.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science
• Knowledge Representation and Reasoning: Preferences

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Web Mining and Content Analysis: Sentiment analysis and opinion mining
• Economics, Online Markets and Human Computation: Social networks and social learning

Abstract

The concept of homophily is pervasive in online social media. While many empirical studies have relied on external sociodemographic traits to investigate it, significantly less is known about homophily at the cognitive level, that is, at the level of shared opinions or values. For such "value homophily", in this paper we study interval-based patterns of opinion homophily from a bounded confidence perspective. We consider three heterogeneous datasets from Reddit and Twitter covering polarizing issues, with user opinions quantified via sentiment analysis and fact-checking, and analyze the interaction networks formed by weaker (reply-based) and stronger (follow-based) social ties. Our findings show that users' interaction neighborhoods are significantly more concentrated in opinion space than expected by chance, with tie strength and issue polarization further amplifying this effect. Moreover, users often exhibit asymmetric tolerance ranges, with asymmetry typically directed toward locally mainstream positions rather than more radical or opposing ones. These findings support a bounded confidence interpretation of online value homophily.

Problem

• opinion homophily
• bounded confidence
• online social networks
• value homophily
• polarizing issues

Innovation

• opinion homophily
• bounded confidence
• sentiment analysis
• social tie strength
• asymmetric tolerance