Print Email Facebook Twitter Misinformation Detection on Social Media Title Misinformation Detection on Social Media: Challenges and the Road Ahead Author Ahvanooey, Milad Taleby (Nanjing University) Zhu, Mark Xuefang (Nanjing University) Mazurczyk, Wojciech (Warsaw University of Technology) Choo, Kim Kwang Raymond (The University of Texas at San Antonio) Conti, M. (TU Delft Cyber Security; Università degli Studi di Padova) Zhang, Jing (Nanjing University of Science and Technology) Date 2022 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. To reference this document use: http://resolver.tudelft.nl/uuid:0609ba1c-06b2-4ca6-8dfa-835babe75f6a DOI https://doi.org/10.1109/MITP.2021.3120876 Embargo date 2022-08-21 ISSN 1520-9202 Source IT Professional, 24 (1), 34-40 Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2022 Milad Taleby Ahvanooey, Mark Xuefang Zhu, Wojciech Mazurczyk, Kim Kwang Raymond Choo, M. Conti, Jing Zhang Files PDF Misinformation_Detection_ ... _Ahead.pdf 1.45 MB Close viewer /islandora/object/uuid:0609ba1c-06b2-4ca6-8dfa-835babe75f6a/datastream/OBJ/view