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Titlebook: Disinformation, Misinformation, and Fake News in Social Media; Emerging Research Ch Kai Shu,Suhang Wang,Huan Liu Book 2020 Springer Nature

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發(fā)表于 2025-3-21 18:02:07 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Disinformation, Misinformation, and Fake News in Social Media
副標(biāo)題Emerging Research Ch
編輯Kai Shu,Suhang Wang,Huan Liu
視頻videohttp://file.papertrans.cn/282/281345/281345.mp4
概述Covers an interdisciplinary emerging research topic on disinformation and misinformation attracting increasing attention.Contains recent advanced social computing, data mining, and machine learning me
叢書名稱Lecture Notes in Social Networks
圖書封面Titlebook: Disinformation, Misinformation, and Fake News in Social Media; Emerging Research Ch Kai Shu,Suhang Wang,Huan Liu Book 2020 Springer Nature
描述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.
出版日期Book 2020
關(guān)鍵詞Fake news; Social media mining; Social cyber security; misinformation and disinformation; community dete
版次1
doihttps://doi.org/10.1007/978-3-030-42699-6
isbn_softcover978-3-030-42701-6
isbn_ebook978-3-030-42699-6Series ISSN 2190-5428 Series E-ISSN 2190-5436
issn_series 2190-5428
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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板凳
發(fā)表于 2025-3-22 00:47:30 | 只看該作者
https://doi.org/10.1007/978-3-030-42699-6Fake news; Social media mining; Social cyber security; misinformation and disinformation; community dete
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發(fā)表于 2025-3-22 08:14:50 | 只看該作者
978-3-030-42701-6Springer Nature Switzerland AG 2020
5#
發(fā)表于 2025-3-22 10:24:13 | 只看該作者
Bots, Elections, and Social Media: A Brief Overview of bots around major political events, including elections in various countries. In this chapter, we summarize our findings of bot operations in the context of the 2016 and 2018 US Presidential and Midterm elections and the 2017 French Presidential election.
6#
發(fā)表于 2025-3-22 15:14:54 | 只看該作者
Kai Shu,Suhang Wang,Huan LiuCovers an interdisciplinary emerging research topic on disinformation and misinformation attracting increasing attention.Contains recent advanced social computing, data mining, and machine learning me
7#
發(fā)表于 2025-3-22 20:48:20 | 只看該作者
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發(fā)表于 2025-3-22 22:50:29 | 只看該作者
https://doi.org/10.1007/978-0-230-00094-0e spread of disinformation and fake news can cause detrimental societal effects. Despite the recent progress in detecting disinformation and fake news, it is still non-trivial due to its complexity, diversity, multi-modality, and costs of fact-checking or annotation. The goal of this chapter is to p
9#
發(fā)表于 2025-3-23 03:03:16 | 只看該作者
https://doi.org/10.1007/978-0-230-00094-0itter users based on their role identities. We first collect a coarse-grained public figure dataset automatically, then manually label a more fine-grained identity dataset. We propose a hierarchical self-attention neural network for Twitter user role identity classification. Our experiments demonstr
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發(fā)表于 2025-3-23 08:36:10 | 只看該作者
Systems Collaboration and Integrationine social networks are used as a means to spread digital deception within local, national, and global communities which has led to a renewed focus on the means of detection and defense. The audience (i.e., social media users) form the first line of defense in this process and it is of utmost import
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