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Review of Offensive Language Detection on Social Media: Current Trends and Opportunities

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Emerging Trends and Applications in Artificial Intelligence ( ICETAI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 960))

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Abstract

Offensive language is defined as derogatory or obscene language that has various forms such as hate speech or cyberbullying. Automated detection of offensive language gains traction due to the high and growing scale of social media user input. In this paper, we provide an overview of the field including background and recent research with a focus on natural language processing. We present a synopsis on the ambiguity in definition and categorization of offensive language, application areas of an automated system, shared tasks organized in this field, dataset creation, model evolution in time through machine learning and deep learning algorithms. Finally challenges and gaps in research are discussed.

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Notes

  1. 1.

    https://www.statista.com/topics/1164/social-networks/dossierKeyfigures.

  2. 2.

    https://www.coe.int/en/web/european-commission-against-racism-and-intolerance/ecri-glossary.

  3. 3.

    https://thelawdictionary.org/offensive-language/.

  4. 4.

    https://www.un.org/en/hate-speech/understanding-hate-speech/what-is-hate-speech.

  5. 5.

    https://www.stopbullying.gov/cyberbullying/what-is-it.

  6. 6.

    https://store.businessinsider.com/products/the-content-moderation-report.

  7. 7.

    https://knowledge.wharton.upenn.edu/article/social-media-firms-moderate-content/.

  8. 8.

    https://competitions.codalab.org/competitions/33835.

  9. 9.

    https://competitions.codalab.org/competitions/34344.

  10. 10.

    https://webtribunal.net/blog/meme-statistics/gref.

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Acknowledgments

We acknowledge support from the Maria de Maeztu Units of Excellence Programme CEX2021-001195-M, funded by MICIU/AEI /10.13039/50110001103 and with the support from Departament de Recerca i Universitats de la Generalitat de Catalunya (ajuts SGR-Cat 2021).

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  1. Department of Information and Communication Technologies, Pompeu Fabra University, C/Tànger, 122, 08018, Barcelona, Spain

    Lütfiye Seda Mut Altın & Horacio Saggion

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  1. Lütfiye Seda Mut Altın
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Correspondence to Lütfiye Seda Mut Altın .

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  1. Ingenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain

    Fausto Pedro García Márquez

  2. National University of Computer and Emerging Sciences, Islamabad, Pakistan

    Akhtar Jamil

  3. Department of Computer Engineering, Istinye University, Istanbul, Türkiye

    Alaa Ali Hameed

  4. Ingenium Research Group, University of Castilla-La Mancha (UCLM), Ciudad Real, Spain

    Isaac Segovia Ramírez

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Mut Altın, L.S., Saggion, H. (2024). Review of Offensive Language Detection on Social Media: Current Trends and Opportunities. In: García Márquez, F.P., Jamil, A., Hameed, A.A., Segovia Ramírez, I. (eds) Emerging Trends and Applications in Artificial Intelligence. ICETAI 2023. Lecture Notes in Networks and Systems, vol 960. Springer, Cham. https://doi.org/10.1007/978-3-031-56728-5_6

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