Survey on Link Anomaly Detection for Textual Stream in Online Social Network

Link anomaly detection is one of the most important topics in social network. Many of the social networks such as Facebook, Google+, LinkedIn, or twitter require an effective and efficient framework to identify deviated data. Anomaly detection methods are typically implemented in social stream mode, and thus cannot be easily extended to large-scale problems without sacrificing computation where the user's link is generated dynamically (replies, mentions, and retweets). A new approach model i.e. probability model, this model to the capture normal linking behavior of a social network users, and propose to detect the trending topic from the social networks through the probability model.