Identifying Hate Speech Through Syntax Dependency Graph Convolution and Sentiment Knowledge Transfer
Author:
Affiliation:
1. School of Computer Science and Technology, Xinjiang Normal University, Ürümqi, China
2. School of Software, Xinjiang University, Ürümqi, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Xinjiang Uygur Autonomous Region
National Natural Science Foundation Young Investigator Grant Program
Xinjiang Normal University’s 2022 Young Top-Notch Talent Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10374337.pdf?arnumber=10374337
Reference42 articles.
1. Hate speech;Nockleby,2020
2. Detecting Offensive Language in Social Media to Protect Adolescent Online Safety
3. Automated Hate Speech Detection and the Problem of Offensive Language
4. A Lexicon-based Approach for Hate Speech Detection
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1. Enhancing Multilingual Hate Speech Detection: From Language-Specific Insights to Cross-Linguistic Integration;IEEE Access;2024
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