Text mining has become a vital zone that has been attached to some examined ranges such as computational etymology, data mining, and information recovery (IR). Almost all people today use social networking activities in their daily interactions with no sorting. This can result in a range of inconsistencies, including lexical, semantic, linguistic, and syntactic ambiguities, making it difficult to determine the accurate data arrangement. Fittingly, the study identified the concept of text mining in terms of its impact on social networks. This study highlights the positive impact of intelligent techniques and how to use text mining to detect the news credibility on Facebook. The study introduced a background that highlighted the related aspects, the relation between these domains, and the news credibility. The study also presents the recent research in these fields with demonstrating the roles of these techniques for the required study target. The study could support as the foundation of future text mining studies on social networks data.
TopIntroduction
Social networks helped people to communicate easily without obstacles (Mukerji, 2018). News and information spread rapidly regardless of the news credibility (Liu, Wang, & Huang, 2018). People who had unpleasant experience or even just heard about it without making sure or checking would create fake news and spread rumors widely for different purposes (Othman, Hassan, Moawad, & Idrees, 2016). This survey discusses the researches considering the detection of fake news, news credibility and how they measured the news credibility and accuracy of news and information. Different models and techniques such as text mining applied techniques helps to detect credibility (Xu, Wang, Wang, & Yang, 2020), (Liu, Wang, & Huang, 2018). Within the past decade, the propagation of network permitted the electronic devices the impulse of social networks hardly. Users of social networks change from the foremost prepared to the foremost energetic periods, and the mass selection of this appliance has given the users a site within the knowledge society (Othman, Hassan, Moawad, & Idrees, 2018). The end user that holds devices to use social networks propagates peculiarity and newsworthiness about current events. It is especially veritable for the most youthful period that based on heightening on social networks to retain overhauled and share results near their method of considering (Mohsen, Hassan, & Idrees, 2016).
On numerous events, it has been demonstrated that this collective information is valuable in case of emergency and harming occasions as fires and storms (Mohsen, Hassan, & Idrees2016). Electronic devices and the successive surge of web clients made a vital impact on the social society. At the time of social networks, the end user that handles these devices is the real reason for spreading peculiarity and newsworthiness nearly specific news. Presently and after, that this sort of declaring is one-sided due to the level of the user's data of the matter or to fulfill an impartial. The ability to share different users' post intensify this wonder and have a cascading type of influence that can prompt the dispersal of false information (Sayed, Salem, & Khedr, 2019). The proposed procedure attempts to deal with this impediment by cross-relating content streams with contrasting heterogeneous degrees of enduring quality (De Maio, Fenza, Gallo, Loia, & Volpe, 2020), in the past, the improvement of social networking sites unimaginably has empowered how people interact with others through networks.
People who use social networks share information and data and interact with other each other. So they are taught from the trends happening on social networks as news and public events (Idrees & Ibrahim, 2018). In any case, most of the information that appears on social networks afterward is unreliable and, in some cases, deceptive. Such substance is called false news. Fake news on the internet as (social networking sites) has the empower to create significant issues in the realworld society (Zhang & Ghorbani, 2019).
Because of substantial investments in the field of innovation by the evolution of social networking sites, the importance of text mining has grown. According to (Kim & Chung, 2018),
(Sultan, Khedr, Idrees, & Kholeif, 2017), data mining and detection of knowledge are currently interesting for experts and researchers. There is also requirements for modifying raw data into useful information and knowledge which lead to awareness (Hassan & Idrees, 2010). The world of business has understood the value of data, information, and derived (knowledge) from copious amounts of data. A range of surveys were composed from different papers to be analyzed and utilized in this outline such as in (Idrees & Ibrahim, 2015). The following sections provide a background for the vital terms, then the relation between the news credibility and intelligent techniques are discussed.