On the Credential Analysis of Social Network Data

The innovative existence of social network has revolutionized the way we communicate, perceive, and interact with others. Internet has become a medium that connects our lives together and attracts many people to spend time with it, and to engage in different activities from casual to business. However, not everyone is trustworthy. One of the main issues in online social networks is the information overload. Some user accounts may be created with hidden agenda and not represent actual people. Our aim in this paper is to develop and test a method for evaluate the credibility of online users based on their interactions with others. We propose an analysis method that uses several analytic measurements for ranking users in Social Networks based on the reputation models such as PageRank, SocialRank, TwitterRank and MetricRank. We also utilize content classification to improve the ranking effectiveness and integrate them to evaluate the consistency of interaction dialogues.