Data Science for Fake News

Deepak P is an Assistant Professor of Computer Science at Queen’s University Belfast, UK. Prior to this, he was a research scientist at IBM Research. His research interests include ethics for machine learning, natural language processing, and information retrieval. He is a senior member of the IEEE and the ACM, and has authored 90+ publications and is an inventor on 10+ patents.Tanmoy Chakraborty is an Assistant Professor at the Department of Computer Science and Engineering, IIIT Delhi, India. Prior to this, he was a postdoctoral associate at University of Maryland, College Para, USA. His research interests include data mining, social media analysis and natural language processing.Cheng Long is an Assistant Professor at the School of Computer Science and Engineering, Nanyang Technological University, Singapore. From 2016 to 2018, he worked as a lecturer at Queen's University Belfast, UK. His research interests are in data management, data mining and machine learning.Santhosh Kumar G is a full Professor at the Department of Computer Science, Cochin University of Science and Technology, Kerala, India. His research interests include cyber physical systems, machine learning and natural language processing.

• 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.