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Published in:
2021 | OriginalPaper | Chapter
Multi-modal Fake News Detection
Author : Tanmoy Chakraborty
Published in: Data Science for Fake News
Publisher: Springer International Publishing
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The primary motivation behind the spread of fake news is to convince the readers to believe false information related to certain events or entities. Human cognition tends to consume news more when it is visually depicted through multimedia content than just plain text. Fake news spreaders leverage this cognitive state to prepare false information in such a way that it looks attractive in the first place. Therefore, multi-modal representation of fake news has become highly popular. This chapter presents a thorough survey of the recent approaches to detect multi-modal fake news spreading on various social media platforms. To this end, we present a list of challenges and opportunities in detecting multi-modal fake news. We further provide a set of publicly available datasets, which is often used to design multi-modal fake news detection models. We then describe the proposed methods by categorizing them through a taxonomy.