Entropy Dynamics of Community Alignment in the Italian Parliament Time-Dependent Network

TL;DR

This paper introduces a novel entropy-based framework to analyze the temporal dynamics of community alignment in political networks, applied to the Italian Parliament, revealing significant structural changes over time.

Contribution

It presents a new entropy-based approach to study community dynamics in time-dependent networks, specifically applied to political voting behavior.

Findings

Detected meso-scale structural changes with entropy measures

Observed increased group alignment entropy after political conflicts

Identified shifts in node alignment entropy post government transition

Abstract

Complex institutions are typically characterized by meso-scale structures which are fundamental for the successful coordination of multiple agents. Here we introduce a framework to study the temporal dynamics of the node-community relationship based on the concept of community alignment, a measure derived from the modularity matrix that defines the alignment of a node with respect to the core of its community. The framework is applied to the 16th legislature of the Italian Parliament to study the dynamic relationship in voting behavior between Members of the Parliament (MPs) and their political parties. As a novel contribution, we introduce two entropy-based measures that capture politically interesting dynamics: the group alignment entropy (over a single snapshot), and the node alignment entropy (over multiple snapshots). We show that significant meso-scale changes in the time-dependent network structures can be detected by a combination of the two measures. We observe a steady growth of the group alignment entropy after a major internal conflict in the ruling majority and a different distribution of nodes alignment entropy after the government transition.