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.

翻译：欧洲右翼民粹主义的兴起凸显了分析社交媒体话语对于理解极端意识形态传播及其政治影响的重要性。Twitter作为互动与动员的平台，为观察极右翼支持者的日常交流提供了独特窗口。本文提出一种方法论，结合前沿自然语言处理技术与社会学视角，分析包含英语和法语极右翼推文的MIGR-TWIT语料库。我们旨在揭示右翼与极右翼行为体围绕移民议题的话语模式、仇恨言论及说服策略。通过融合语言学、社会学与计算分析方法，本研究试图为社会动态提供跨学科见解，并促进对社交媒体平台上右翼极端主义所引发当代挑战的深入理解。