Coalition Structure and Polarization in Parliamentary Voting Networks: Evidence from the Italian Parliament

2026-02-03

AI Summary

This study addresses how to uncover latent voting coalitions and polarization dynamics in parliaments beyond formal party affiliations. Proposing a multiscale network analysis framework that integrates modularity, voting distance, and betweenness centrality, the work systematically characterizes hidden alliance structures and their evolution in the Italian Parliament (2018–2021) using only publicly available roll-call vote data. It pioneers the application of multiscale network methods to parliamentary politics, revealing that the technocratic government, while broadly supported, exhibited low polarization; that issue-based polarization was shaped by opposition fragmentation; and that approximately 2% of legislators served as critical bridges across groups. The analysis further identifies multiple undeclared voting blocs, offering a reproducible, data-driven paradigm for understanding informal political coordination.

Technology Category

• Game Theory and Economic Paradigms: Social Choice / Voting
• Humans and AI: Voting
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining

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
• Responsible Web: Social and technical mechanisms of refusal for web technologies and applications

Abstract

Ensuring legislative accountability in multi-party systems requires quantitative tools that reveal actual voting behavior beyond formal party affiliations. We present a network-based framework for analyzing parliamentary dynamics at multiple scales, capturing coalition structure, group coherence, and individual influence. Applied to over 4 million vote expressions from the Italian Parliament across three government formations (2018-2021), the methodology combines network modularity, voting distance metrics, and betweenness centrality to map the structure of collective decision-making. Using this framework, we show that system-level polarization, as captured by network modularity, varies systematically with coalition structure rather than coalition size. Technical governments display paradoxically lower global polarization despite broader formal support, reflecting structurally mixed voting patterns rather than unified blocs. On polarizing issues such as immigration, network polarization depends strongly on the fragmentation or cohesion of the opposition, even when the governing coalition votes cohesively. Betweenness analysis reveals that mediator roles are highly concentrated, with only about 2% of parliamentarians acting as structural bridges between communities. Community detection further uncovers implicit coalitions that are not apparent from declared alliances. The framework relies exclusively on public roll-call data, enabling reproducible analysis and direct applicability to any legislature with transparent voting records. By linking individual voting behavior to emergent system-level structure, the methodology provides quantitative infrastructure for comparative analysis of legislative voting networks and coalition monitoring, enabling systematic assessment of legislative behaviour.

Problem

• coalition structure
• polarization
• parliamentary voting networks
• legislative accountability
• multi-party systems

Innovation

• voting networks
• coalition structure
• network modularity
• betweenness centrality
• polarization