Text and Social Media Analytics for Fake News and Hate Speech Detection
eBook - ePub

Text and Social Media Analytics for Fake News and Hate Speech Detection

  1. 324 pages
  2. English
  3. ePUB (mobile friendly)
  4. Only available on web
eBook - ePub

Text and Social Media Analytics for Fake News and Hate Speech Detection

Book details
Table of contents
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About This Book

Identifying and stopping the dissemination of fabricated news, hate speech, or deceptive information camouflaged as legitimate news poses a significant technological hurdle. This book presents emergent methodologies and technological approaches of natural language processing through machine learning for counteracting the spread of fake news and hate speech on social media platforms.

ā€¢ Covers various approaches, algorithms, and methodologies for fake news and hate speech detection.

ā€¢ Explains the automatic detection and prevention of fake news and hate speech through paralinguistic clues on social media using artificial intelligence.

ā€¢ Discusses the application of machine learning models to learn linguistic characteristics of hate speech over social media platforms.

ā€¢ Emphasizes the role of multilingual and multimodal processing to detect fake news.

ā€¢ Includes research on different optimization techniques, case studies on the identification, prevention, and social impact of fake news, and GitHub repository links to aid understanding.

The text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.

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Yes, you can access Text and Social Media Analytics for Fake News and Hate Speech Detection by Hemant Kumar Soni,Sanjiv Sharma,G. R. Sinha in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Engineering. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Chapman and Hall/CRC
Year
2024
ISBN
9781040100509
Edition
1
Topic
Computer Science
Subtopic
Computer Engineering
Index
Computer Science

Table of contents

  1. Cover
  2. Half-Title
  3. Title
  4. Copyright
  5. Dedication
  6. Contents
  7. Preface
  8. Acknowledgment
  9. About the Editors
  10. Contributors
  11. Introduction
  12. Chapter 1 Analysis of Fake News Detection and Prevention of Various Fake News Detection Algorithms and their Research Challenges
  13. Chapter 2 Detection and Prevention of Fake News and Hate Speech through Machine Learning and Natural Language Processing
  14. Chapter 3 Detection of Fake News on Elections Using a Machine Learning Approach
  15. Chapter 4 Analytics of Text and Social Media for Challenges of Hateful and Offensive Speech Detection
  16. Chapter 5 The Ripple Effect of Fake News and Hate Speech on Elections and Its Countermeasures Using Machine Learning Methodologies: A Critical Analysis
  17. Chapter 6 Explainable Models for the Detection of Incidents of Fake News and Hate Speech
  18. Chapter 7 Gender Biases and Politics: The Semiotics of Hate Speech on the Internet
  19. Chapter 8 Social Media Platforms and COVID-19-Related Misinformation in India: Acceptance, Spread, and Implications
  20. Chapter 9 SIR Model for Understanding the Spread of Fake News and Hate Speech
  21. Chapter 10 Impact on Fake News in Social Media and Current Technology in Detection of Fake News
  22. Chapter 11 Connotative Meaning of Political Emotive Expressions in Arab Spring Fake News
  23. Chapter 12 Detecting Fake News and Hate Speech Using Machine Learning: An Overview of Frameworks
  24. Chapter 13 Hate Content Identification in Code-mixed Social Media Data
  25. Chapter 14 Social Media Skirmish: Dealing With Fake News and Propaganda Using AI and ML
  26. Chapter 15 Detection and Prevention of Fake News and Hate Speech through Machine Learning and Natural Language Processing
  27. Chapter 16 Fake News and Hate Speech: Influence on Society and Detection by Machine Learning
  28. Index