Chengzhang Zhu1, 2, Wentao Zhao2, *, Qian Li1, Pan Li2, Qiaobo Da3
CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 317-333, 2019, DOI:10.32604/cmc.2019.05677
Abstract Detecting collaborative fraudsters who manipulate opinions in social media is becoming extremely important in order to provide reliable information, in which, however, the diversity in different groups of collaborative fraudsters presents a significant challenge to existing collaborative fraudsters detection methods. These methods often detect collaborative fraudsters as the largest group of users who have the strongest relation with each other in the social media, consequently overlooking the other groups of fraudsters that are with strong user relation yet small group size. This paper introduces a novel network embedding-based framework NEST and its instance BEST to address this issue. NEST detects… More >
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