Open AccessFuzzy‐based fake information detection algorithm to define the user trust on the content of social networks
Author(s) -
Nirmala Munirathinam,
Babu Madda Rajasekhara
Publication year - 2019
Publication title -
iet networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 21
ISSN - 2047-4962
DOI - 10.1049/iet-net.2018.5208
Subject(s) - computer science , anonymity , globe , social media , social network (sociolinguistics) , reliability (semiconductor) , fuzzy logic , internet privacy , content (measure theory) , world wide web , computer security , artificial intelligence , psychology , mathematics , mathematical analysis , power (physics) , physics , quantum mechanics , neuroscience
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.