MLHS-CGCapNet: A Lightweight Model for Multilingual Hate Speech Detection-Reference-Cited by-同舟云学术

MLHS-CGCapNet: A Lightweight Model for Multilingual Hate Speech Detection

Published:2024 Issue: Volume:12 Page:106631-106644
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kousar Abida¹^ORCID,Ahmad Jameel²^ORCID,Ijaz Khalid¹^ORCID,Yousef Amr³^ORCID,Ahmed Shaikh Zaffar⁴^ORCID,Khosa Ikramullah⁵^ORCID,Chavali Durga⁶^ORCID,Anjum Mohd⁷^ORCID

Affiliation:

1. Department of Artificial Intelligence, School of Systems and Technology, University of Management and Technology, Lahore, Pakistan

2. Department of Computer Science, School of Systems and Technology, University of Management and Technology, Lahore, Pakistan

3. Electrical Engineering Department, University of Business and Technology, Jeddah, Saudi Arabia

4. Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi, Pakistan

5. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan

6. Trinity Health, Trinity Information Services, Livonia, MI, USA

7. Department of Computer Engineering, Aligarh Muslim University, Aligarh, India

Funder

University of Management and Technology, Lahore, Pakistan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10613616.pdf?arnumber=10613616

Reference29 articles.

1. Towards Hate Speech Detection at Large via Deep Generative Modeling

2. Results of the PolEval 2019 shared task 6: First dataset and open shared task for automatic cyberbullying detection in polish Twitter;Ptaszynski

3. Model-Agnostic Meta-Learning for Multilingual Hate Speech Detection

4. Cross-lingual Capsule Network for Hate Speech Detection in Social Media

5. SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter