Contribution Classification Methods for Fake News Using Machine Learning

Author:

Nikoukar Marzieh,Heidari Safanaz

Publisher

Springer Nature Switzerland

Reference42 articles.

1. Nadereh, H., Azam, A.,:Identifying influential nodes in rumor propagation on social networks, 2nd National Conference on Industrial Management, Astaneh Ashrafiyeh (2017)

2. Elaheh, R., Babak, A.Q.:2017, Proposing a combined model of weed-fire for information dissemination in social networks. In: 14th International Conference on Industrial Engineering, Tehran

3. Mohammadreza, Z., Zahra, R.: Improving fake news detection in news media using topic modeling-based methods and deep learning algorithms. In: 9th National Conference on Electrical, Computer, and Mechanical Engineering, Shirvan (2020)

4. Safura, S., Dehkordi,, Nadri, Sadri Karami, S.K., Akram, 2019, Rumor detection in social networks using maximum entropy and deep learning, 6th National Conference on Applied Research in Computer Engineering and Information Technology, Tehran

5. Shabani, K., Geranmayepour, A., Hashemi, S.: Ways to detect fake news in the media from the point of view of communication specialists and professionals. New Med. Stud. 8(30), 207–233 (2022)

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