Fake News Detection Using Supervised Machine Learning Classification Algorithms
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-7402-1_65
Reference16 articles.
1. Granik M, Mesyura V (2017) Fake news detection using naive Bayes classifier. In: 2017 IEEE 1st Ukraine conference on electrical and computer engineering UKRCON, pp 900–903. https://doi.org/10.1109/UKRCON.2017.8100379
2. Ahmed H, Traore I, Saad S (2017) Detection of online fake news using N-Gram analysis and machine learning techniques. In: Traore I, Woungang I, Awad A (eds) Intelligent, secure, and dependable systems in distributed and cloud environments, pp 127–138. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-319-69155-8_9
3. Campan A, Cuzzocrea A, Truta TM (2017) Fighting fake news spread in online social networks: actual trends and future research directions. Presented at the December 1. https://doi.org/10.1109/BigData.2017.8258484
4. Pérez-Rosas V, Kleinberg B, Lefevre A, Mihalcea R (2018) Automatic detection of fake news. COLING 2018 - 27th Int. Conf. Comput. Linguist. Proc. 3391–3401 (2018). https://doi.org/10.48550/arXiv.1708.07104
5. Aphiwongsophon S, Chongstitvatana P (2018) Detecting fake news with machine learning method. In: 2018 15th International conference on electrical engineering/electronics, computer, telecommunications and information technology (ECTI-CON), pp 528–531. IEEE, Chiang Rai, Thailand. https://doi.org/10.1109/ECTICon.2018.8620051.
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