Political Homophily in Independence Movements: Analysing and Classifying Social Media Users by National Identity

TL;DR

This paper presents a method to classify social media users supporting or opposing independence movements by analyzing their network connections, revealing strong homophily effects and achieving high classification accuracy across three territories.

Contribution

It introduces a scalable, language-independent approach to classify users based on their social network interactions in independence movements.

Findings

Homophily significantly influences social media connections in independence contexts.

Follow network-based classifiers achieve 85-97% accuracy.

The methodology is applicable across different languages and territories.

Abstract

Social media and data mining are increasingly being used to analyse political and societal issues. Here we undertake the classification of social media users as supporting or opposing ongoing independence movements in their territories. Independence movements occur in territories whose citizens have conflicting national identities; users with opposing national identities will then support or oppose the sense of being part of an independent nation that differs from the officially recognised country. We describe a methodology that relies on users' self-reported location to build large-scale datasets for three territories -- Catalonia, the Basque Country and Scotland. An analysis of these datasets shows that homophily plays an important role in determining who people connect with, as users predominantly choose to follow and interact with others from the same national identity. We show that a classifier relying on users' follow networks can achieve accurate, language-independent classification performances ranging from 85% to 97% for the three territories.