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Abstract
With the tremendous proliferation of social media in day-to-day life, social content has become one of the potential information sources. Ensuring social trust is crucial to averting the negative impact on viral marketing, expertise retrieval, and recommendation systems, leading to ascertainment of credibility of social media users. A unified framework is proposed for evaluation of the user credibility through analysis of three fundamental credibility-related factors from social media and e-commerce sites, namely, probability of being a promoter, a spam bot, and/or a spammer. The factors are estimated using deep learning baseline model and/or further analysed using Fuzzy Inference System for making a decision on Tweeter credibility. The framework is demonstrated on Twitter and Amazon benchmark datasets for evaluating its efficacy in identifying credible users. The proposed system outperformed the baseline model and state-of-the-art techniques providing an accuracy of 97% in detecting the credible user.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
K. Laila
K Laila received her BE degree in computer science and engineering from the CSI Institute of Technology, Thovalai, India in 2008, ME degree in computer science and engineering from the National Engineering College, Kovilpatti, India, in 2010. She is currently pursuing the PhD degree in the Department of Computer Technology, at MIT campus, Anna University, Chennai, India. Her research interest includes social network analysis, information retrieval, soft computing and pattern recognition. Email: [email protected]
P. Jayashree
Jayashree Padmanabhan received her BE (Hons) in electronics and communication from Madurai Kamaraj University, Masters (electronics engineering), and PhD (computer science and engineering) from Anna University. She is currently working as an associate professor in the Department of Computer Technology, Anna University, Chennai. She has rich teaching and research experience and has published nearly 50 journal/conference papers. Her research interests include cyber security, cryptographic algorithms, data analytics, medical informatics, and e-learning.
V. Vinuvarsidh
V Vinuvarsidh received the BTech degree in computer science and engineering from MIT, Anna University, Chennai, India. He is currently working as a web developer in Zoho Corporation, Chennai. His research interests include recommendation system, cloud computing, and machine learning. Email: [email protected]