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Fusion: Practice and Applications
Volume 4 , Issue 1, PP: 41-57 , 2021 | Cite this article as | XML | Html |PDF

Title

Fusion of Machine learning for Detection of Rumor and False Information in Social Network

  Nehal Mostafa 1 * ,   Ibrahim El-henawy 2 ,   Ahmed Sleem 3

1  Department of Computer Science, Zagazig university, Sharqiyah, Egypt
    (nihal.nabil@zu.edu.eg)

2   Faculty of Computers and Informatics, Zagazig University, Sharqiyah, Egypt
    (ielhenawy@zu.edu.eg)

3  Faculty of Computers and Informatics, Zagazig University, Sharqiyah, Egypt
    (ahmedsleem8000@gmail.com)


Doi   :   https://doi.org/10.54216/FPA.040105

Received: February 16, 2021 Accepted: Jun 15, 2021

Abstract :

In recent years, spreading social media platforms and mobile devices led to more social data, advertisements, political opinions, and celebrity news proliferating fake news. Fake news can cause harm to networks, communications, and users and cause trust issues toward government, healthcare, or social media platforms. This inspired many researchers to implement models to detect falsified information content. But there are still many issues that need to be discussed and explored. In our paper, we introduce categories of fake news detection methods and compare these methods. After that, the promising applications for false news detection are extensively discussed in terms of fake account detection, bot detection, bullying detection, and security and privacy of social media. After all, A thorough discussion of the potential of machine learning approaches for fake news detection and interventions in social networks along with the state-of-the-art challenges, opportunities, and future search prospects. This article seeks to aid the readers and researchers in explaining the motive and role of the different machine learning fusion paradigms to offer them a comprehensive realization of unexplored issues related to false information and other scenarios of social networks.

Keywords :

fake news; social networks; machine learning; false information; networks; social media; fusion

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Cite this Article as :
Style #
MLA Nehal Mostafa , Ibrahim El-henawy , Ahmed Sleem. "Fusion of Machine learning for Detection of Rumor and False Information in Social Network." Fusion: Practice and Applications, Vol. 4, No. 1, 2021 ,PP. 41-57 (Doi   :  https://doi.org/10.54216/FPA.040105)
APA Nehal Mostafa , Ibrahim El-henawy , Ahmed Sleem. (2021). Fusion of Machine learning for Detection of Rumor and False Information in Social Network. Journal of Fusion: Practice and Applications, 4 ( 1 ), 41-57 (Doi   :  https://doi.org/10.54216/FPA.040105)
Chicago Nehal Mostafa , Ibrahim El-henawy , Ahmed Sleem. "Fusion of Machine learning for Detection of Rumor and False Information in Social Network." Journal of Fusion: Practice and Applications, 4 no. 1 (2021): 41-57 (Doi   :  https://doi.org/10.54216/FPA.040105)
Harvard Nehal Mostafa , Ibrahim El-henawy , Ahmed Sleem. (2021). Fusion of Machine learning for Detection of Rumor and False Information in Social Network. Journal of Fusion: Practice and Applications, 4 ( 1 ), 41-57 (Doi   :  https://doi.org/10.54216/FPA.040105)
Vancouver Nehal Mostafa , Ibrahim El-henawy , Ahmed Sleem. Fusion of Machine learning for Detection of Rumor and False Information in Social Network. Journal of Fusion: Practice and Applications, (2021); 4 ( 1 ): 41-57 (Doi   :  https://doi.org/10.54216/FPA.040105)
IEEE Nehal Mostafa, Ibrahim El-henawy, Ahmed Sleem, Fusion of Machine learning for Detection of Rumor and False Information in Social Network, Journal of Fusion: Practice and Applications, Vol. 4 , No. 1 , (2021) : 41-57 (Doi   :  https://doi.org/10.54216/FPA.040105)