Disinformation, misinformation, and fake news in social media : emerging research challenges and opportunities /: emerging research challenges and opportunities. ([2020])

• Record Type: Book
• Further Information: Note: Kai Shu [and three others], editors.
• Editors: Shu, Kai
• Contents: Intro -- Acknowledgment -- Contents -- Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements -- 1 Information Disorder -- 1.1 Fake News as an Example of Disinformation -- 2 The Power of Weak Social Supervision -- 2.1 Understanding Disinformation with WSS -- 2.2 Detecting Disinformation with WSS -- 3 Recent Advancements: An Overview of Chapter Topics -- 4 Looking Ahead -- 4.1 Explanatory Methods -- 4.2 Neural Fake News Generation and Detection -- 4.3 Early Detection of Disinformation -- 4.4 Cross Topics Modeling on Disinformation -- References Part I User Engagements in the Dissemination of Information Disorder -- Discover Your Social Identity from What You Tweet: A Content Based Approach -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Word Embedding -- 3.2 Bi-LSTM -- 3.3 Attention -- 3.4 Final Classification -- 4 Experiments -- 4.1 Dataset -- 4.2 Hyperparameter Setting -- 4.3 Baselines -- 4.4 Results -- 4.5 Transfer Learning for Fine-Grained Identity Classification -- 4.6 Case Study -- 4.7 Error Analysis -- 5 Discussion and Conclusion -- References -- User Engagement with Digital Deception -- 1 Methods and Materials 1.1 Attributing News Sources -- 1.2 Inferring User Account Types: Automated Versus Manual -- 1.3 Predicting User Demographics -- 1.4 Measuring Inequality of User Engagement -- 1.5 Predicting User Reactions to Deceptive News -- 1.6 Data -- 2 Who Engages with (mis) and (dis)information? -- 2.1 The Population Who Engage with Misinformation and Disinformation -- 2.2 Automated Versus Manual Accounts -- 2.3 Sockpuppets: Multiple Accounts for Deception -- 2.4 Demographic Sub-populations -- 3 What Kind of Feedback Do Users Provide? -- 3.1 Across Multiple Platforms 3.2 Across User-Account Characteristics -- 4 How Quickly Do Users Engage with (mis) and (dis)information? -- 4.1 Across Multiple Platforms -- 4.2 Across User-Account Characteristics -- 4.3 Demographic Sub-populations -- 5 Discussion and Conclusions -- References -- Characterization and Comparison of Russian and Chinese Disinformation Campaigns -- 1 Introduction -- 2 Literature Review -- 2.1 Russia Internet Research Agency Data -- 2.2 Chinese Manipulation of Hong Kong Narrative -- 3 Data -- 4 Characterization and Comparison -- 4.1 Network -- 4.2 History of Accounts -- 4.3 Geography of Accounts 4.4 Calculating Content Marketshare Over Time -- 4.5 Bot Analysis -- 4.6 Multi-media Analysis -- 4.7 State Sponsored Accounts -- 5 How Many Similar Actors are Left? -- 6 Conclusion -- References -- Pretending Positive, Pushing False: Comparing Captain Marvel Misinformation Campaigns -- 1 Introduction -- 2 Related Work -- 3 Data Description and Methods -- 4 Results -- 4.1 Diffusion on Twitter -- 4.2 Originating and Responding Twitter Communities -- 4.3 Types of Actors -- 5 Discussion and Conclusions -- References -- Bots, Elections, and Social Media: A Brief Overview -- 1 Introduction
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 302.23/1; Fake news; Disinformation; Social media; Electronic books
• Languages: English
• ISBNs: 9783030426996; 3030426998
• Related ISBNs: 303042698X; 9783030426989
• Notes: Note: Includes bibliographical references and index.; Note: Description based on online resource; title from digital title page (viewed on June 30, 2020).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.