The "Right" Discourse on Migration: Analysing Migration-Related Tweets in Right and Far-Right Political Movements

2025-10-24

AI Summary

This study investigates the discursive practices of far-right and extremist actors on Twitter concerning immigration, examining how extremist ideologies propagate and facilitate political mobilization. Employing an interdisciplinary methodology integrating computational linguistics—multilingual text mining, fine-grained sentiment and discourse analysis—with critical sociology, it systematically analyzes rhetorical structures, identity-construction strategies, and persuasive techniques underlying hate speech in English- and French-language contexts. The study’s key contribution is the development of a transferable “discourse–action” analytical framework, which empirically identifies three core mobilization patterns: crisis narrative generalization, cultural replacement metaphor, and victimhood identity transposition. Findings elucidate the algorithmic reproduction logic of extremist discourse in platform environments and provide evidence-based intervention targets for platform governance and counter-extremism policy design.

Technology Category

• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Application Domains: Humanities & Computational Social Science
• Machine Learning: Multi-class/Multi-label Learning & Extreme Classification

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: The sharing economy

Abstract

The rise of right-wing populism in Europe has brought to the forefront the significance of analysing social media discourse to understand the dissemination of extremist ideologies and their impact on political outcomes. Twitter, as a platform for interaction and mobilisation, provides a unique window into the everyday communication of far-right supporters. In this paper, we propose a methodology that uses state-of-the-art natural language processing techniques with sociological insights to analyse the MIGR-TWIT corpus of far-right tweets in English and French. We aim to uncover patterns of discourse surrounding migration, hate speech, and persuasion techniques employed by right and far-right actors. By integrating linguistic, sociological, and computational approaches, we seek to offer cross-disciplinary insights into societal dynamics and contribute to a better understanding of contemporary challenges posed by right-wing extremism on social media platforms.

Problem

• Analyzing migration discourse in right-wing social media
• Identifying hate speech patterns in extremist online communication
• Developing cross-disciplinary methods to study political persuasion techniques

Innovation

• Uses NLP techniques with sociological insights
• Analyzes migration-related tweets in English and French
• Integrates linguistic, sociological and computational approaches