ConFake: fake news identification using content based features
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15792-1.pdf
Reference69 articles.
1. Ahmed, H (2017) Detecting opinion spam and fake news using n-gram analysis and semantic similarity. PhD thesis, University of Victoria
2. Ahmed, H, Traore, I, Saad, S (2017) Detection of online fake news using n-gram analysis and machine learning techniques. In: Intelligent, secure, and dependable systems in distributed and cloud environments: first international conference, ISDDC 2017, Vancouver, BC, Canada, October 26-28, 2017, Proceedings 1, Springer, pp 127–138
3. Ajao, O, Bhowmik, D, Zargari, S (2018) Fake news identification on twitter with hybrid cnn and rnn models. In: Proceedings of the 9th international conference on social media and society, pp 226–230
4. Allcott H, Gentzkow M (2017) Social media and fake news in the 2016 election. J Econ Perspec 31(2):211–236
5. Bali, APS, Fernandes, M, Choubey, S, Goel, M (2019) Comparative performance of machine learning algorithms for fake news detection. In: Advances in computing and data sciences: third international conference, ICACDS 2019, Ghaziabad, India, April 12–13, 2019, Revised Selected Papers, Part II 3, Springer, pp 420–430
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