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Disinformation, Misinformation, and Fake News in Social Media
Emerging Research Challenges and Opportunities
eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9783030426996
Veröffentl:
2020
Einband:
eBook
Seiten:
288
Autor:
Kai Shu
Serie:
Lecture Notes in Social Networks
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:
This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges, learn state-of-the-art solutions for their specific needs, and quickly identify new research problems in their domains. The contributors to this volume describe the recent advancements in three related parts: (1) user engagements in the dissemination of information disorder; (2) techniques on detecting and mitigating disinformation; and (3) trending issues such as ethics, blockchain, clickbaits, etc. This edited volume will appeal to students, researchers, and professionals working on disinformation, misinformation and fake news in social media from a unique lens.
This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges, learn state-of-the-art solutions for their specific needs, and quickly identify new research problems in their domains. The contributors to this volume describe the recent advancements in three related parts: (1) user engagements in the dissemination of information disorder; (2) techniques on detecting and mitigating disinformation; and (3) trending issues such as ethics, blockchain, clickbaits, etc. This edited volume will appeal to students, researchers, and professionals working on disinformation, misinformation and fake news in social media from a unique lens.
A Social Network Analysis and Cyber Forensics Informed Exploration of Disinformation Campaigns.- Mitigating Fake News through Fact-checking URL recommendation.- Detecting Fake News with Semi-supervised Tensor Decomposition.- Learning Hierarchical Discourse-level Structure for Fake News Detection.- Mining Styles and Emotions for Fake News Detection.- Fake News Detection with Deep Diffusive Network Model.- Fake News Detection: An Interdisciplinary Research.- Jointly Identifying Framing Bias and Detecting Fake News on Social Media.