Survey on Fake News Detection Techniques
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-51859-2_31
Reference16 articles.
1. Bovet, A., Makse, H.A.: Influence of fake news in Twitter during the 2016 US presidential election. Nat. Commun. 10, 7 (2019). https://doi.org/10.1038/s41467-018-07761-2
2. Ahn, Y.-C., Jeong, C.-S.: Natural language contents evaluation system for detecting fake news using deep learning. In: 2019 16th International Joint Conference on Computer Science and Software Engineering (JCSSE) (2019). https://doi.org/10.1109/jcsse.2019.8864171
3. Bhutani, B., Rastogi, N., Sehgal, P., Purwar, A.: Fake news detection using sentiment analysis. In: 2019 Twelfth International Conference on Contemporary Computing (IC3) (2019). https://doi.org/10.1109/ic3.2019.8844880
4. Kim, K.-H., Jeong, C.-S.: Fake news detection system using article abstraction. In: 2019 16th International Joint Conference on Computer Science and Software Engineering (JCSSE) (2019). https://doi.org/10.1109/jcsse.2019.8864154
5. Girgis, S., Amer, E., Gadallah, M.: Deep learning algorithms for detecting fake news in online text. IEEE (2018). 978-1-5386-5111-7/18/$31.00
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