1 option
Disinformation, Misinformation, and Fake News in Social Media : Emerging Research Challenges and Opportunities / edited by Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in social networks 2190-5428
- Lecture Notes in Social Networks, 2190-5428
- Language:
- English
- Subjects (All):
- Data mining.
- Social sciences--Data processing.
- Social sciences.
- Social sciences--Computer programs.
- Application software.
- Social media.
- Journalism.
- Data Mining and Knowledge Discovery.
- Computational Social Sciences.
- Computer Appl. in Social and Behavioral Sciences.
- Social Media.
- Local Subjects:
- Data Mining and Knowledge Discovery.
- Computational Social Sciences.
- Computer Appl. in Social and Behavioral Sciences.
- Social Media.
- Journalism.
- Physical Description:
- 1 online resource (VIII, 288 pages) : 84 illustrations, 73 illustrations in color.
- Edition:
- First edition 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- 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, et cetera This edited volume will appeal to students, researchers, and professionals working on disinformation, misinformation and fake news in social media from a unique lens.
- Contents:
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-42699-6
- 9783030426996
- Access Restriction:
- Restricted for use by site license.
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