An Experimental Technique on Fake News Detection in Online Social Media
Mahamat Adam Boukhari1, Milind Gayakwad2
1Mahamat Adam Boukhari, PG Student, Bharati Vidyapeeth (Deemed to be University), College of Engineering, India.
2Prof. Milind Gayakwad Professor, Bharati Vidyapeeth (Deemed to be University), College of Engineering, India.
Manuscript received on 09 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 08 July 2019 | PP: 526-530 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H11200688S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Social media is a double-edged sword for news consumption. On the one side, its low price, simple access and fast data dissemination lead individuals to search and consume social media news. On the other side, this is allows the wide dissemination of fake news,T. low quality news with intentionally false information. The widespread dissemination of false news has the ability to impact people and society highly negatively… Therefore, the detection of false news in recently, social media has become a study that attracts tremendous attention. False news of Detection Unique in the social media features and difficulties that make algorithms available for detection of traditional Ineffective or non-applicable media. First, the false news is deliberately written to deceive readers into believing false data and information, making it t dissects and not trivial in order to detect news content, we need to include information Auxiliary, as the social commitments of users in helping to create a determination for social media. Second, this extra data and information is challenging in and of itself social commitments of the users with false news produce data which are large, incomplete, unstructured and that’s loud. Because the issue of identifying fake news in social media is both difficult and meaningful, we performed this study to promote further research into the issue.. This study provides a thorough overview of the detection of fak social media news, including fake psychological and social theory news characteristics, current information mining algorithms. assessment metrics and representative datasets we also address associated fields of studies, open issues and future directions for the detection of fake news on social media. We also discuss related research areas, open problems, and future research directions for fake news detection on social media.
Keywords: Fake News, User Profile, Trust Analysis;
Scope of the Article: Social Networks