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- Vol. 7 Issue 4
- Article
Interpretable AI-Enhanced Machine Learning for Intelligent Spambot and Fake Followers Identification
Authors
1 PG Scholar, Department of Computer Science and Engineering, UCEK, JNTUK, Kakinada, Andhra Pradesh, India. 2 Professor, Department of Computer Science and Engineering, UCEK, JNTUK, Kakinada, Andhra Pradesh, India.
Article Information
- Published In
- Volume 7, Issue 4 (2026)
- Published Online
- July-August 2026
- Pages
- 246-257
- Article Type
- Original Article
References
1. S. N. Tirumala Rao, Sireesha Moturi, Najeer Shaik, Suneetha Mothe, Sistla V. S. Manikanta Rohit, Ravi Lakshmi Sri Harsha, and
Dodda Venkata Reddy, “Fake Profile Detection Using Machine Learning,”2025.
2. Rajat Soni, Shubham Jain, and Ankit Kumar, “Fake Twitter Followers Detection Using Machine Learning Approach,”2020.
3. M. Santhoshi, S. Sailaja, and J. Jyotsna, “Deep Learning Approach for Identification of Fake Profiles in Social Media,”2023
4. Murtala Aminu Buhari, Salau Ayodeji Olalekan, Azadeh Mohammadi, and Mo Saraee, “A Comparative Study on the Characteristics
and Behaviours of Social Media Users in Response to Fake News on X (Twitter),”2024.
5. Sarith Imaduwage, P. P. N. V. Kumara, and W. J. Samaraweera, “Importance of User Representation in Propagation Network-based
Fake News Detection: A Critical Review and Potential Improvements,”2022.
6. Andrea Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, and Maurizio Tesconi, “Detecting Fake Profiles on Social
Networks: A Systematic Investigation,”, 202
7. S. K. Lakshmanaprabu, K. Shankar, M. Ilayaraja, S. S. Kumar, and N. Arunkumar, “Constructing a User-Centered Fake News
Detection Model by Using Classification Algorithms in Machine Learning Techniques,”2019.
8. Matsumoto Hayato, Soh Yoshida, and Mitsuji Muneyasu, “Flexible Framework to Provide Explainability for Fake News Detection
Methods on Social Media,”in 2022.
9. A. S. Bandi, P. S. Reddy, and K. R. Reddy, “Detection of Fake Users in Twitter Using Network Representation and NLP,”2022.
10. Sara Asghari, Mostafa Haghir Chehreghani, and Morteza Haghir Chehreghani, “On Using Node Indices and Their Correlations for
Fake Account Detection,”in 2022
11. Ryo Onuma, Hiroaki Kaminaga, Hiroki Nakayama, Youzou Miyadera, Keito Suzuki, and Shoichi Nakamura, “Analysis of Articles
that Correct Other Posts on Social Media Aimed at Promoting the Experience in Examining Fakes,”in 2022.
12. Kai Shu, Suhang Wang, and Huan Liu, “Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks,”,
2020.
Dodda Venkata Reddy, “Fake Profile Detection Using Machine Learning,”2025.
2. Rajat Soni, Shubham Jain, and Ankit Kumar, “Fake Twitter Followers Detection Using Machine Learning Approach,”2020.
3. M. Santhoshi, S. Sailaja, and J. Jyotsna, “Deep Learning Approach for Identification of Fake Profiles in Social Media,”2023
4. Murtala Aminu Buhari, Salau Ayodeji Olalekan, Azadeh Mohammadi, and Mo Saraee, “A Comparative Study on the Characteristics
and Behaviours of Social Media Users in Response to Fake News on X (Twitter),”2024.
5. Sarith Imaduwage, P. P. N. V. Kumara, and W. J. Samaraweera, “Importance of User Representation in Propagation Network-based
Fake News Detection: A Critical Review and Potential Improvements,”2022.
6. Andrea Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, and Maurizio Tesconi, “Detecting Fake Profiles on Social
Networks: A Systematic Investigation,”, 202
7. S. K. Lakshmanaprabu, K. Shankar, M. Ilayaraja, S. S. Kumar, and N. Arunkumar, “Constructing a User-Centered Fake News
Detection Model by Using Classification Algorithms in Machine Learning Techniques,”2019.
8. Matsumoto Hayato, Soh Yoshida, and Mitsuji Muneyasu, “Flexible Framework to Provide Explainability for Fake News Detection
Methods on Social Media,”in 2022.
9. A. S. Bandi, P. S. Reddy, and K. R. Reddy, “Detection of Fake Users in Twitter Using Network Representation and NLP,”2022.
10. Sara Asghari, Mostafa Haghir Chehreghani, and Morteza Haghir Chehreghani, “On Using Node Indices and Their Correlations for
Fake Account Detection,”in 2022
11. Ryo Onuma, Hiroaki Kaminaga, Hiroki Nakayama, Youzou Miyadera, Keito Suzuki, and Shoichi Nakamura, “Analysis of Articles
that Correct Other Posts on Social Media Aimed at Promoting the Experience in Examining Fakes,”in 2022.
12. Kai Shu, Suhang Wang, and Huan Liu, “Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks,”,
2020.
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