Fuzzy‐based fake information detection algorithm to define the user trust on the content of social networks. Issue 6 (1st November 2019)

• Record Type: Journal Article
• Authors: Nirmala, Munirathinam; Babu, Madda Rajasekhara
• Is Part Of: IET networks. Volume 8:Issue 6(2019)
• Page Start: 367
• Page End: 371
• Publication Date: 2019-11-01
• Subjects: social networking (online) -- trusted computing -- fuzzy set theory; user trust -- online social networks -- social network content -- information creators -- fuzzy detection algorithm -- trustable content -- social media -- Twitter social network platform -- fuzzy‐based fake information detection algorithm; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2018.5208
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : Across the globe, right from people who are technologically naive to people who are with high‐technical knowledge, use, share, spread, and connect with each other through online social networks. People start believing and sharing the social network content without any proof of its authenticity. In several cases, the reliability of the information that gets shared between the users remains questionable due to the anonymity of the information creators. In this work, a fuzzy detection algorithm is proposed to identify the trustable content in social media. The proposed methodology is evaluated on Twitter social network platform. By computing the predictive measures, the efficiency of the proposed approach is well established.