Data Science for Fake News: Surveys and Perspectives (Paperback)

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.