Format:
1 Online-Ressource(VIII, 288 p. 84 illus., 73 illus. in color.)
Edition:
1st ed. 2020.
ISBN:
9783030426996
Series Statement:
Lecture Notes in Social Networks
Content:
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.
Content:
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.
Additional Edition:
ISBN 9783030426989
Additional Edition:
ISBN 9783030427009
Additional Edition:
ISBN 9783030427016
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783030426989
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783030427009
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783030427016
Language:
English
DOI:
10.1007/978-3-030-42699-6
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