A Framework for Early Detection of Cyberbullying in Chinese-English Code-Mixed Social Media Text Using Natural Language Processing and Machine Learning

This study develops a new expert system framework to address the issue of early detection of cyberbullying incidents in Chinese-English code-mixed language on social media networks. The framework covers the crawling of session-based social media texts with potential cyberbullying messages with a cro...

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Bibliographic Details
Published in2023 5th International Conference on Natural Language Processing (ICNLP) pp. 298 - 302
Main Authors Chu, Carlin Chun-Fai, So, Raymond, Li, Simon Siu-Wai, Kwong, Ernest Kan-Lam, Chiu, Chun-Hung
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2023
Subjects
Crowdsourcing
Cyberbullying
Expert systems
explainable AI
Machine learning algorithms
Natural language processing
NLP
Shapley value
Transfer learning
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Summary:This study develops a new expert system framework to address the issue of early detection of cyberbullying incidents in Chinese-English code-mixed language on social media networks. The framework covers the crawling of session-based social media texts with potential cyberbullying messages with a crowdsourcing web application to systematically retrieve and manually annotate a cyberbullying dataset, and most importantly establishes an explainable artificial intelligence model based on natural language processing algorithm for identification of targeted emotional colloquial slang phrases and machine learning method using Shapley value and transfer learning approach for automatic early detection of cyberbullying incidents in Chinese-English codemixed language.
DOI:10.1109/ICNLP58431.2023.00061