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

Lipase

书目名称Disinformation, Misinformation, and Fake News in Social Media影响因子(影响力)




书目名称Disinformation, Misinformation, and Fake News in Social Media影响因子(影响力)学科排名




书目名称Disinformation, Misinformation, and Fake News in Social Media网络公开度




书目名称Disinformation, Misinformation, and Fake News in Social Media网络公开度学科排名




书目名称Disinformation, Misinformation, and Fake News in Social Media被引频次




书目名称Disinformation, Misinformation, and Fake News in Social Media被引频次学科排名




书目名称Disinformation, Misinformation, and Fake News in Social Media年度引用




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paroxysm

Diatribe

https://doi.org/10.1007/978-3-030-42699-6Fake news; Social media mining; Social cyber security; misinformation and disinformation; community dete

Atmosphere

978-3-030-42701-6Springer Nature Switzerland AG 2020

行乞

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.

搬运工

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

搬运工

手段

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

idiopathic

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

bioavailability

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