Overview
- Proposes new models, practical solutions, and technological advances related to the detection and analysis of fake news
- Combines theory and practice so that readers find a description of the concepts and context
- Brings together different chapters of authors and professionals in a way to provide readers with solid theoretical basis
Part of the book series: Studies in Computational Intelligence (SCI, volume 1001)
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Table of contents (21 chapters)
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Front Matter
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Machine Learning Techniques and Fake News
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Front Matter
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Case Studies and Frameworks
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Front Matter
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Keywords
About this book
This book presents the latest cutting-edge research, theoretical methods, and novel applications in the field of computational intelligence techniques and methods for combating fake news. Fake news is everywhere. Despite the efforts of major social network players such as Facebook and Twitter to fight disinformation, miracle cures and conspiracy theories continue to rain down on the net. Artificial intelligence can be a bulwark against the diversity of fake news on the Internet and social networks.
This book discusses new models, practical solutions, and technological advances related to detecting and analyzing fake news based on computational intelligence models and techniques, to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence techniques. Further, the book helps readers understand computational intelligence techniques combating fake news in a systematic and straightforward way.
Editors and Affiliations
Bibliographic Information
Book Title: Combating Fake News with Computational Intelligence Techniques
Editors: Mohamed Lahby, Al-Sakib Khan Pathan, Yassine Maleh, Wael Mohamed Shaher Yafooz
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-90087-8
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-90086-1Published: 16 December 2021
Softcover ISBN: 978-3-030-90089-2Published: 17 December 2022
eBook ISBN: 978-3-030-90087-8Published: 15 December 2021
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIII, 435
Number of Illustrations: 21 b/w illustrations, 135 illustrations in colour
Topics: Computational Intelligence, Social Media, Artificial Intelligence, Data Engineering, Big Data