Fine-Tuned Understanding: Enhancing Social Bot Detection With Transformer-Based Classification-Reference-Cited by-同舟云学术

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Fine-Tuned Understanding: Enhancing Social Bot Detection With Transformer-Based Classification

Published:2024 Issue: Volume:12 Page:118250-118269
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Sallah Amine¹^ORCID,Arbi Abdellaoui Alaoui El²^ORCID,Agoujil Said³,Ahmad Wani Mudasir⁴^ORCID,Hammad Mohamed⁴^ORCID,Maleh Yassine⁵^ORCID,Abd El-Latif Ahmed A.⁴^ORCID

Affiliation:

1. Department of Computer Science, Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, Errachidia, Morocco

2. Department of Sciences, Ecole Normale Supérieure, Moulay Ismail University of Meknes, Errachidia, Morocco

3. École Nationale de Commerce et de Gestion, Moulay Ismail University of Meknes, El Hajeb, Morocco

4. EIAS Data Science Laboratory, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

5. Laboratory laSTI, ENSAK, Sultan Moulay Slimane University (USMS), Beni Mellal, Morocco

Funder

Prince Sultan University through the Article Processing Charges

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10630818.pdf?arnumber=10630818

Reference96 articles.

1. Adversarial Attacks on Deep-learning Models in Natural Language Processing

2. Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-Based Detection

3. Machine learning-based social media bot detection: a comprehensive literature review

4. Cyberbullying Detection using Machine Learning

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