DEA-RNN: A Hybrid Deep Learning Approach for Cyberbullying Detection in Twitter Social Media Platform

Author:

Murshed Belal Abdullah Hezam1ORCID,Abawajy Jemal2ORCID,Mallappa Suresha1,Saif Mufeed Ahmed Naji3ORCID,Al-Ariki Hasib Daowd Esmail4ORCID

Affiliation:

1. Department of Studies in Computer Science, Mysore University, Mysore, Karnataka, India

2. School of Information Technology, Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, VIC, Australia

3. Department of Computer Applications, Sri Jayachamarajendra College of Engineering, (Affiliated to VTU), JSS TI Campus, Mysore, Karnataka, India

4. Department of Computer Networks and Distributed Systems, Al Saeed faculty for Engineering and Information Technology, Taiz University, Taiz, Yemen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

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1. Deep learning approach to detect cyberbullying on twitter;Multimedia Tools and Applications;2024-07-23

2. Arabic cyberbullying detection system using convolutional neural network and multi-head attention;International Journal of Speech Technology;2024-07-06

3. A comprehensive review of cyberbullying-related content classification in online social media;Expert Systems with Applications;2024-06

4. Revealing Online Threats Through Leveraging RNN Models for Advanced Cyberbullying Detection;2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET);2024-05-16

5. Detecting Cyberbullying through social media: A Deep Learning Approach;2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE);2024-05-16

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