Data science for fake news : surveys and perspectives

Data science for fake news : surveys and perspectives / Deepak P, Tanmoy Chakraboty, Cheng Long, Santhosh Kumar G.

This book provides an overview of fake news detection, both through a variety of tutorial-style survey articles that capture advancements in the field from various facets and in a somewhat unique direction through expert perspectives from various disciplines. The approach is based on the idea that a...

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Bibliographic Details
Main Authors: P, Deepak (Author), Chakraborty, Tanmoy (Author), Long, Cheng (Author), G, Santhosh Kumar (Author)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, [2021]
Series:Information retrieval series ; 42.
Subjects:
Fake news.
Journalism > Data processing.
Data mining.
Journalistic ethics.
Data mining
Fake news
Journalism > Data processing
Journalistic ethics
Online Access:Click for online access
Table of Contents:
  • A Multifaceted Approach to Fake News
  • Part I: Survey. On Unsupervised Methods for Fake News Detection ; Multi-modal Fake News Detection ; Deep Learning for Fake News Detection ; Dynamics of Fake News Diffusion ; Neural Language Models for (Fake?) News Generation ; Fact Checking on Knowledge Graphs ; Graph Mining Meets Fake News Detection
  • Part II: Perspectives. Fake News in Health and Medicine ; Ethical Considerations in Data-Driven Fake News Detection ; A Political Science Perspective on Fake News ; A Political Science Perspective on Fake News ; Fake News and Social Processes: A Short Review ; Misinformation and the Indian Election: Case Study ; STS, Data Science, and Fake News: Questions and Challenges ; Linguistic Approaches to Fake News Detection.

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