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Portuguese Far-Right Discourse on Social Media: Insights from Topic Modeling

Authors Mauro Cardoso , Eugénio Ribeiro , Fernando Batista

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Subject Classification

ACM Subject Classification
  • Computing methodologies → Natural language processing
  • Human-centered computing → Social network analysis
  • Computing methodologies → Topic modeling
  • Computing methodologies → Language resources
  • Applied computing → Sociology
Keywords
  • Political Discourse
  • Topic Modeling
  • Far-Right
  • CHEGA (Portugal)
  • Social Media

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Abstract

This study analyzes the social media discourse of leading figures from Portugal’s far right party CHEGA, examining 10,323 posts on X (formerly Twitter) published between late 2019 and mid‑2024. Using BERTopic, 59 latent topics clustered into two main discursive dynamics were found: (1) ideological and public, and (2) party, electoral and parliamentary related. Within the first dynamic, we conducted a focused sub-analysis of themes related with identity, immigration and security narratives - topics that display posting peaks around electoral cycles, suggesting the strategic use of emotionally charged, identitarian frames for political mobilization. The model exhibits strong topic coherence and lexical diversity, indicating its robustness in extracting thematic structures from politically polarized microtexts. Nevertheless, our findings are constrained by source, the absence of interaction metrics, and the unmet need to link online discourse to offline events. This study demonstrates how computational topic modeling can reveal strategic communication patterns in far-right political discourse and underscores the need for cross-platform and interaction-level research to assess broader societal impact.

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Mauro Cardoso, Eugénio Ribeiro, and Fernando Batista. Portuguese Far-Right Discourse on Social Media: Insights from Topic Modeling. In 14th Symposium on Languages, Applications and Technologies (SLATE 2025). Open Access Series in Informatics (OASIcs), Volume 135, pp. 12:1-12:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/OASIcs.SLATE.2025.12

Author Details

Mauro Cardoso
  • Instituto Universitário de Lisboa (ISCTE-IUL), Portugal
  • INESC-ID Lisboa, Portugal
Eugénio Ribeiro
  • Instituto Universitário de Lisboa (ISCTE-IUL), Portugal
  • INESC-ID Lisboa, Portugal
Fernando Batista
  • Instituto Universitário de Lisboa (ISCTE-IUL), Portugal
  • INESC-ID Lisboa, Portugal

Funding

This work was supported by Portuguese national funds through Fundação para a Ciência e a Tecnologia (FCT) (Reference: UIDB/50021/2020, DOI: 10.54499/UIDB/50021/2020).

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