Why Are Some Countries More Politically Fragmented Online Than Others?

2026-01-08

arXiv.org

AI Summary

This study addresses the absence of a unified framework for measuring and comparing online political fragmentation across countries and multiparty systems. It proposes the first structural measure of political fragmentation, integrating multiscale community detection with effective branching factors to analyze co-follow networks of 18,325 political influencers on Twitter/X in Brazil, Spain, and the United States. The findings reveal that Brazil exhibits the highest level of fragmentation, particularly among left-wing actors; Spain and the U.S. show comparable overall fragmentation, yet the left is more fragmented in Spain while the right is more fragmented in the U.S.; and lower fragmentation is associated with stronger alignment between social identity and ideology. This approach offers a scalable quantitative tool for cross-national research on political polarization.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Security and Privacy: Large-scale security measurements

Abstract

Online political divisions, such as fragmentation or polarization, are a growing global concern that can foster radicalization and hinder democratic cooperation; however, not all divisions are detrimental, some reflect pluralism and healthy diversity of opinion in a democracy. While prior research has predominantly focused on polarization in the United States, there remains a limited body of research on political divides in multiparty systems, and no universal method for comparing fragmentation across countries. Moreover, cross-country comparison is rare. This study first develops a novel measure of structural political fragmentation built on multi-scale community detection and the effective branching factor. Using a dataset of 18,325 political influencers from Brazil, Spain, and the United States, we assess online fragmentation in their Twitter/X co-following networks. We compare the fragmentation of the three countries, as well as the ideological groups within each. We further investigate factors associated with the level of fragmentation in each country. We find that political fragmentation differs across countries and is asymmetric between ideological groups. Brazil is the most fragmented, with higher fragmentation among the left-wing group, while Spain and the United States exhibit similar overall levels, with the left more fragmented in Spain and the right more fragmented in the United States. Additionally, we find that social identity plays a central role in political fragmentation. A strong alignment between ideological and social identities, with minimal overlap between ideologies, tends to promote greater integration and reduce fragmentation. Our findings provide explanations for cross-national and ideological differences in political fragmentation.

Problem

• political fragmentation
• online polarization
• cross-country comparison
• multiparty systems
• social identity

Innovation

• structural political fragmentation
• multi-scale community detection
• effective branching factor
• cross-national comparison
• co-following networks