Multi-level framework for anomaly detection in social networking

The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).,Author first reviewed the related work, and then, the research model designed was explained. Furthermore, the details regarding Levels 1 and 2 were narrated.,By using the proposed technique, FScore obtained for Twitter and Facebook data set was 96.22 and 94.63, respectively.,Four data sets were used for the experiment and the acquired outcomes demonstrate enhancement over the current existing frameworks.,This paper designed a multilevel framework that can be used to detect the anomalies present in the OSN.

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