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Ex-ThaiHate: A Generative Multi-task Framework for Sentiment and Emotion Aware Hate Speech Detection with Explanation in Thai

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Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track (ECML PKDD 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14174))

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Abstract

Social media platforms have both positive and negative impacts on users in diverse societies. One of the adverse effects of social media platforms is the usage of hate and offensive language, which not only fosters prejudice but also harms the vulnerable. Additionally, a person’s sentiment and emotional state heavily influence the intended content of any social media post. Despite extensive research being conducted to detect online hate speech in English, there is a lack of similar studies on low-resource languages such as Thai. The recent enactment of laws like the “right to explanations” in the General Data Protection Regulation has stimulated the development of interpretable models rather than solely focusing on performance. Motivated by this, we created the first benchmark hate speech corpus, called Ex-ThaiHate, in the Thai language. Each post is annotated with four labels, namely hate, sentiment, emotion, and rationales (explainability), which specify the phrases that are responsible for annotating the post as hate. In order to investigate the effect of sentiment and emotional information on detecting hate speech posts, we propose a unified generative framework called GenX, which redefines this multi-task problem as a text-to-text generation task to simultaneously solve four tasks: hate-speech identification, rationale detection, sentiment, and emotion detection. Our extensive experiments demonstrate that GenX significantly outperforms all baselines and state-of-the-art models, thereby highlighting its effectiveness in detecting hate speech and identifying the rationales in low-resource languages. The code and dataset are available at https://github.com/dsmlr/Ex-ThaiHate.

Disclaimer: The article contains offensive text and profanity. This is due to the nature of the work and does not reflect any opinion or stance of the authors.

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Notes

  1. 1.

    https://pythainlp.github.io/docs/2.2/.

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Acknowledgments

This work was supported by the Ministry of External Affairs (MEA) and the Department of Science & Technology (DST), India, under the ASEAN-India Collaborative R &D Scheme.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, 801103, India

    Krishanu Maity, Shaubhik Bhattacharya & Sriparna Saha

  2. School of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand

    Salisa Phosit, Sawarod Kongsamlit & Kitsuchart Pasupa

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  1. Krishanu Maity
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  2. Shaubhik Bhattacharya
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Correspondence to Kitsuchart Pasupa .

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Editors and Affiliations

  1. CENTAI, Turin, Italy

    Gianmarco De Francisci Morales

  2. NYU and Two Sigma, New York, NY, USA

    Claudia Perlich

  3. Netflix, Los Angeles, CA, USA

    Natali Ruchansky

  4. Telefonica Research, Barcelona, Spain

    Nicolas Kourtellis

  5. Politecnico di Torino, Turin, Italy

    Elena Baralis

  6. CENTAI, Turin, Italy

    Francesco Bonchi

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Maity, K., Bhattacharya, S., Phosit, S., Kongsamlit, S., Saha, S., Pasupa, K. (2023). Ex-ThaiHate: A Generative Multi-task Framework for Sentiment and Emotion Aware Hate Speech Detection with Explanation in Thai. In: De Francisci Morales, G., Perlich, C., Ruchansky, N., Kourtellis, N., Baralis, E., Bonchi, F. (eds) Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track. ECML PKDD 2023. Lecture Notes in Computer Science(), vol 14174. Springer, Cham. https://doi.org/10.1007/978-3-031-43427-3_9

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