Disinformation, Misinformation, and Fake News in Social Media Emerging Research Challenges and Opportunities /
Disinformation, Misinformation, and Fake News in Social Media Emerging Research Challenges and Opportunities / [electronic resource] :
edited by Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu.
- 1st ed. 2020.
- VIII, 288 p. 84 illus., 73 illus. in color. online resource.
- Lecture Notes in Social Networks, 2190-5436 .
- Lecture Notes in Social Networks, .
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.
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.
9783030426996
10.1007/978-3-030-42699-6 doi
Data mining.
Sociology--Methodology.
Social sciences--Data processing.
Social media.
Journalism.
Data Mining and Knowledge Discovery.
Sociological Methods.
Computer Application in Social and Behavioral Sciences.
Social Media.
Journalism.
QA76.9.D343
006.312
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.
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.
9783030426996
10.1007/978-3-030-42699-6 doi
Data mining.
Sociology--Methodology.
Social sciences--Data processing.
Social media.
Journalism.
Data Mining and Knowledge Discovery.
Sociological Methods.
Computer Application in Social and Behavioral Sciences.
Social Media.
Journalism.
QA76.9.D343
006.312