Machine Learning Approaches for Rumor Detection in Social Media: Types, Techniques, and Opportunities
Authors
Afrin Akter Mim1, Minhajul Islam Mim2, Md Ahasan Habib3, Dipanita Mondol1, *, Md Sabbir Ahamed4, Sudeepta Chandra Paul5
1Department of Computer Science and Engineering, Daffodil International University, Dhaka, 1216, Bangladesh
2Information and Communication Engineering, Hohai University, Nanjing, P. R. China
3Computer Science and Technology, Hohai University, Nanjing, P. R. China
4Management Information Systems, Lamar University, Beaumont, United States
5Department of Computer Science and Engineering, Jagannath University, Dhaka, Bangladesh
*Corresponding author.
Email: mondaldipanwita827@gmail.com
Corresponding Author
Dipanita Mondol
Available Online 8 June 2026.
- DOI
- 10.2991/978-94-6239-664-7_71How to use a DOI?
- Keywords
- Rumor detection; social media; machine learning approaches
- Abstract
The trend of spreading false news or rumors has kept pace with the growing utilization of social media. Hatred and fear spread through rumors, which are extremely harmful to society. As social media continues to grow, rumor detection has become an increasingly important research area. In this paper, we summarize the efforts made thus far on this topic. We provide an overview of rumors from different dimensions, existing methods, and machine learning and network-based approaches used to distinguish rumors, evaluate method performance, and, importantly, discuss several new directions for future research.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Afrin Akter Mim AU - Minhajul Islam Mim AU - Md Ahasan Habib AU - Dipanita Mondol AU - Md Sabbir Ahamed AU - Sudeepta Chandra Paul PY - 2026 DA - 2026/06/08 TI - Machine Learning Approaches for Rumor Detection in Social Media: Types, Techniques, and Opportunities BT - Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025) PB - Atlantis Press SP - 1040 EP - 1051 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6239-664-7_71 DO - 10.2991/978-94-6239-664-7_71 ID - Mim2026 ER -