An intelligent cybersecurity system for detecting fake news in social media websites

People worldwide suffer from fake news in many life aspects, healthcare, transportation, education, economics, and many others. Therefore, many researchers have considered seeking techniques for automatically detecting fake news in the last decade. The most popular news agencies use e-publishing on...

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Bibliographic Details
Main Author: Zitar, Raed (author)
Other Authors: Mughaid, Ala (author), Al-Zu'bi, Shadi (author), Arjan, A (author), Al-Amrat, Rula (author), Alajmi, Rathaa (author), Abualigah, Laith (author), Maalej, Ahmed (author)
Published: 2022
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Online Access:https://depot.sorbonne.ae/handle/20.500.12458/1273
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Summary:People worldwide suffer from fake news in many life aspects, healthcare, transportation, education, economics, and many others. Therefore, many researchers have considered seeking techniques for automatically detecting fake news in the last decade. The most popular news agencies use e-publishing on their websites; even websites can publish any news they want. However, thus before quotation any news from a website, there should be a close look at news resource ranking by using a trusted websites classifier, such as the website world rank, which reflects the repute of these websites. This paper uses the world rank of news websites as the main factor of news accuracy by using two widespread and trusted websites ranking. Moreover, a secondary factor is proposed to compute the news accuracy similarity by comparing the current news with fakes news and getting the possible news accuracy. Experiments results are conducted on several benchmark datasets. The results showed that the proposed method got promising results compared to other comparative methods in defining the news accuracy.