Misinformation Detection on Social Media

Challenges and the Road Ahead

Journal article (2022)

Authors

Milad Taleby Ahvanooey Nanjing University
Mark Xuefang Zhu Nanjing University
Wojciech Mazurczyk Warsaw University of Technology
Kim Kwang Raymond Choo The University of Texas at San Antonio
M. Conti Università degli Studi di Padova, Cyber Security - EEMCS
Jing Zhang Nanjing University of Science and Technology
Research Group
Cyber Security (EEMCS) (TU Delft)
Copyright: © 2022 Milad Taleby Ahvanooey, Mark Xuefang Zhu, Wojciech Mazurczyk, Kim Kwang Raymond Choo, M. Conti, Jing Zhang
DOI: https://doi.org/10.1109/MITP.2021.3120876
More Info
expand_more

Published Date

2022

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Cyber Security

Abstract

It is increasingly challenging to deal with the volume,variety, velocity, and veracity of misinformation (e.g., dissemination of fake news contents, spurious posts, and fabricated images/videos) from different online platforms. In this article, we present an overview of existing machine learning and information hiding-based misinformation detection techniques and discuss the current threats and limitations of these approaches. Based on the discussion, we identify a number of potential countermeasures.

Files

Misinformation_Detection_on_So... (.pdf)
(.pdf | 1.45 Mb)
- Embargo expired in 21-08-2022