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Bypassing the Nuances of Portuguese Covert Hate Speech Through Contextual Analysis

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Progress in Artificial Intelligence (EPIA 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14969))

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Abstract

Detecting and addressing covert hate speech poses significant challenges in online platforms where discriminatory messages are often disguised within seemingly innocuous content. In this study, we investigate the effectiveness of contextual analysis in bypassing the nuances of covert hate speech. Our research explores the impact of prompt engineering and context addition on the classification of overt and covert hate speech across diverse target groups, including Roma, migrants, LGBTQ+, and individuals of African descent. Through experimental trials using generative models like GPT-3.5 and GPT-4, our findings reveal that the addition of context, not only improves the overall performance of the models in general hate speech (from 75.0% to 79.6% F1 score, for the positive class), but also significantly improves the classification of covert hate speech, increasing True Positives by 21.64% (absolute) compared to the 6.5% in overt hate speech. Despite these improvements, the addition of context also increased the number of False Positives, indicating that a further refinement is needed for this contextual analysis. Moreover, target group analysis demonstrates a correlation between the prevalence of covert hate speech and model performance.

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Notes

  1. 1.

    https://knowhate.eu/pt-pt/.

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Acknowledgement

This work was funded in part by the European Union under Grant CERV-2021-EQUAL (101049306). However, the views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or Knowhate Project. Neither the European Union nor the Knowhate Project can be held responsible.

Author information

Authors and Affiliations

  1. Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR, Lisbon, Portugal

    Gil Ramos, Pedro Fialho, Sérgio Moro & António Fonseca

  2. Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon, Portugal

    Fernando Batista & Ricardo Ribeiro

  3. INESC-ID, Lisbon, Portugal

    Fernando Batista, Ricardo Ribeiro & Paula Carvalho

  4. University of Jordan, Amman, Jordan

    Sérgio Moro

  5. ISCTE-Instituto Universitário de Lisboa and Center for Psychological Research and Social Intervention (CIS-ISCTE), Lisbon, Portugal

    Rita Guerra

  6. ISCTE-Instituto Universitário de Lisboa and Business Research Unit (BRU-ISCTE), Lisbon, Portugal

    Catarina Marques

  7. ITI-LARSyS and IST, Lisbon, Portugal

    Cláudia Silva

Authors
  1. Gil Ramos
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  2. Fernando Batista
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  3. Ricardo Ribeiro
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  4. Pedro Fialho
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  5. Sérgio Moro
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  6. António Fonseca
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  7. Rita Guerra
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  8. Paula Carvalho
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  9. Catarina Marques
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  10. Cláudia Silva
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Corresponding author

Correspondence to Gil Ramos .

Editor information

Editors and Affiliations

  1. University of Minho, Braga, Portugal

    Manuel Filipe Santos

  2. University of Minho, Braga, Portugal

    José Machado

  3. University of Minho, Braga, Portugal

    Paulo Novais

  4. University of Minho, Braga, Portugal

    Paulo Cortez

  5. Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal

    Pedro Miguel Moreira

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Ramos, G. et al. (2025). Bypassing the Nuances of Portuguese Covert Hate Speech Through Contextual Analysis. In: Santos, M.F., Machado, J., Novais, P., Cortez, P., Moreira, P.M. (eds) Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science(), vol 14969. Springer, Cham. https://doi.org/10.1007/978-3-031-73503-5_20

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  • DOI: https://doi.org/10.1007/978-3-031-73503-5_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-73502-8

  • Online ISBN: 978-3-031-73503-5

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