Exploring the Impact of Lexicon-based Knowledge Transfer for Hate Speech Detection in Indonesia Code-Mixed Languages-Reference-Cited by-同舟云学术

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Exploring the Impact of Lexicon-based Knowledge Transfer for Hate Speech Detection in Indonesia Code-Mixed Languages

Published:2023-12-15 Issue: Volume:1 Page:85-90
ISSN:
Container-title:Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval
language:
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Author:

Pamungkas Endang Wahyu¹^ORCID,Purworini Dian²^ORCID,Priyawati Diah³^ORCID,Chasana Rona Rizkhy Bunga²^ORCID

Affiliation:

1. Informatics Engineering Department, Universitas Muhammadiyah Surakarta, Indonesia and Social Informatics Research Center, Universitas Muhammadiyah Surakarta, Indonesia

2. Communication Science Department, Universitas Muhammadiyah Surakarta, Indonesia and Social Informatics Research Center, Universitas Muhammadiyah Surakarta, Indonesia

3. Informatics Engineering Department, Universitas Muhammadiyah Surakarta, Indonesia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3639233.3639247

Reference22 articles.

1. Ajeng Dwi Asti, Indra Budi, and Muhammad Okky Ibrohim. 2021. Multi-label Classification for Hate Speech and Abusive Language in Indonesian-Local Languages. In 2021 International Conference on Advanced Computer Science and Information Systems (ICACSIS). IEEE, 1–6.

2. Hurtlex: A Multilingual Lexicon of Words to Hurt

3. Irina Bigoulaeva, Viktor Hangya, Iryna Gurevych, and Alexander Fraser. 2023. Label modification and bootstrapping for zero-shot cross-lingual hate speech detection. Language Resources and Evaluation (2023), 1–32.

4. Detecting abusive comments at a fine-grained level in a low-resource language

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