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2017
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(2017): Detecting deceptive engagement in social media by temporal pattern analysis of user behaviors. A survey. In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 7 (5). DOI: 10.1002/widm.1210
Abstract: Deceptive engagement in social media, such as spamming, commenting, or rating with automatic scripts, spreading fabricated facts, seriously affects users' trust on online services. Given the large volumes of information generated by users, effectively spotting users involved such deceptive engagement has become a challenging problem. Recent research has shown that techniques for analyzing temporal behavioral patterns are critical to address such problem. In this study, we survey recent advances in these techniques. We first summarize three approaches to model temporal information. Then, by using representative application examples, we discuss recent approaches with respect to their applications to real-world large-scale social media. With a focus on the temporal perspective, we then discuss advantages and challenges of each approach. (C) 2017 John Wiley & Sons, Ltd
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