A Walk Through Various Paradigms for Fake News Detection on Social Media-Reference-Cited by-同舟云学术

A Walk Through Various Paradigms for Fake News Detection on Social Media

Published:2020-12-21 Issue: Volume: Page:173-183
ISSN:2367-4512
Container-title:Proceedings of International Conference on Computational Intelligence and Data Engineering
language:
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Author:

Divya T. V.^ORCID,Banik Barnali Gupta^ORCID

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-8767-2_16

Reference24 articles.

1. Shu K, Bernard HR, Liu H (2019) Studying fake news via network analysis: detection and mitigation. In: Emerging research challenges and opportunities in computational social network analysis and mining. Springer, Cham, pp 43–65

2. Ahmed H, Traore I, Saad S (2017) Detection of online fake news using N-gram analysis and machine learning techniques. In: International conference on intelligent, secure, and dependable systems in distributed and cloud environments. Springer, Cham, pp 127–138

3. Shu K, Sliva A, Wang S, Tang J, Liu H (2017) Fake news detection on social media: a data mining perspective. ACM SIGKDD Explor Newslett 19(1):22–36

4. Tacchini E, Ballarin G, Della Vedova ML, Moret S, de Alfaro L (2017) Some like it hoax: automated fake news detection in social networks. arXiv:1704.07506

5. Tschiatschek S, Singla A, Gomez Rodriguez M, Merchant A, Krause A (2018) Fake news detection in social networks via crowd signals. In: Companion proceedings of the the web conference 2018, pp 517–524

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