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Erschienen in:
Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Exploring the Role of Visual Content in Fake News Detection

verfasst von : Juan Cao, Peng Qi, Qiang Sheng, Tianyun Yang, Junbo Guo, Jintao Li

Erschienen in: Disinformation, Misinformation, and Fake News in Social Media

Verlag: Springer International Publishing

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Abstract

The increasing popularity of social media promotes the proliferation of fake news, which has caused significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research area of great concern. With the development of multimedia technology, fake news attempts to utilize multimedia content with images or videos to attract and mislead consumers for rapid dissemination, which makes visual content an important part of fake news. Despite the importance of visual content, our understanding about the role of visual content in fake news detection is still limited. This chapter presents a comprehensive review of the visual content in fake news, including the basic concepts, effective visual features, representative detection methods and challenging issues of multimedia fake news detection. This chapter can help readers to understand the role of visual content in fake news detection, and effectively utilize visual content to assist in detecting multimedia fake news.

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Vorheriges Kapitel Tensor Embeddings for Content-Based Misinformation Detection with Limited Supervision
Nächstes Kapitel Credibility-Based Fake News Detection
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Metadaten
Titel
Exploring the Role of Visual Content in Fake News Detection
verfasst von
Juan Cao
Peng Qi
Qiang Sheng
Tianyun Yang
Junbo Guo
Jintao Li
Copyright-Jahr
2020
Buch
Disinformation, Misinformation, and Fake News in Social Media

Print ISBN: 978-3-030-42698-9

Electronic ISBN: 978-3-030-42699-6

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-42699-6_8

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