Comparative Analysis of Fake News Identification Using Machine Learning Methods
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0037-0_23
Reference21 articles.
1. Meyer R (2018) The grim conclusions of the largest-ever study of fake news. The Atlantic 8
2. Devi S, Karthik V, Bavatharani SBV, Indhumadhi K (2021) Fake news and tampered image detection in social networks using machine learning. In: 2021 third international conference on inventive research in computing applications (ICIRCA), IEEE, pp 266–272
3. Jiang TAO, Li JP, Haq AU, Saboor A, Ali A (2021) A novel stacking approach for accurate detection of fake news. IEEE Access 9:22626–22639
4. 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
5. Shu K, Mahudeswaran D, Wang S, Lee D, Liu H (2020) Fakenewsnet: a data repository with news content, social context, and spatiotemporal information for studying fake news on social media. Big Data 8(3):171–188
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