[email protected] +91 9840521421 Scholarly Open Access, Peer-reviewed, Refereed Journal e-ISSN 2582-8746 Since 2020
  1. Home
  2. Archives
  3. 2026
  4. Vol. 7 Issue 4
  5. Article
Original Article

Interpretable AI-Enhanced Machine Learning for Intelligent Spambot and Fake Followers Identification

Open Access Peer Reviewed Crossref DOI

Authors

  • Mattada Venuka1
  • Dr. A. Krishna Mohan2

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 Online
July-August 2026
Pages
246-257
Article Type
Original Article
Check for updates
check update

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.
APC from ₹1200 + 18% GST

Peer-reviewed open access₹1200 Indian (₹1400 with DOI)$80 USD internationalpaid after acceptance Peer-reviewed open access₹1200 Indian$80 USD international ₹1200 Indian · $80 intl

  • CrossRef DOI
  • ISSN 2582-8746
  • Open Access
  • Peer Reviewed
  • Plagiarism Checked
  • Google Scholar
Submit Paper