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Awesome Fake News

This repository contains recent research on fake news. Inspired from other 'awesome' github pages like awesome-deep-learning.

Table of content:

a) Data repository

Kaggle dataet: Getting Real about Fake News

FakeNewsChallenge Fake News Challenge 1

BuzzFeedNews Partisan News Analysis

Data for politifact.com, also check Liar, Liar Pants on Fire: A New Benchmark Dataset for Fake News Detection

Some websites sharing fake articles: https://gist.github.com/Criipi/a3a7357466821f2ec62ce42b2529394b

b) Publications

2017, Rashkin, Hannah, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, and Yejin Choi. "Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking." In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2921-2927. 2017.

2017, Wang, William Yang. Liar, Liar Pants on Fire: A New Benchmark Dataset for Fake News Detection

2017, Shu, Kai, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. "Fake News Detection on Social Media: A Data Mining Perspective." ACM SIGKDD Explorations Newsletter 19, no. 1 (2017): 22-36.

2016, Kumar, Srijan, Robert West, and Jure Leskovec. "Disinformation on the web: Impact, characteristics, and detection of wikipedia hoaxes." In Proceedings of the 25th International Conference on World Wide Web, pp. 591-602. International World Wide Web Conferences Steering Committee, 2016.

2015, Rubin, Victoria L., Yimin Chen, and Niall J. Conroy. "Deception detection for news: three types of fakes." Proceedings of the Association for Information Science and Technology 52, no. 1 (2015): 1-4.

2015, Conroy, Niall J., Victoria L. Rubin, and Yimin Chen. "Automatic deception detection: Methods for finding fake news." Proceedings of the Association for Information Science and Technology 52, no. 1 (2015): 1-4.

2015, Hassan, Naeemul, Chengkai Li, and Mark Tremayne. "Detecting check-worthy factual claims in presidential debates." In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 1835-1838. ACM, 2015.

c) Tutorials

demidovakatya/competitions

d) Useful Websites

Analysis of fake news dataset with Machine Learning

Fake News Challenge

Politifact

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