Identification of Suspicious Patterns in Social Network using Zipf’s Law

Scale-Free social network is universally popular among the users of almost all the ages. This scale-free network follows the Power Law that expresses the distribution of data in the form of body and tail. Tail can be expressed in two types: heavy and long. Heavy tail also called Pareto distribution means rare or infrequent occurrences of events with high values whereas long tail which is used for Zipf's distributionshows many occurrences of events with small values. In this paper, we employed the concept of long tail to identify the skeptical pattern in the social network as security is the main concern for everyone and become an open research area. Earlier papers on Zipf's Law worked on the concept of constructing the dictionaries or thesaurus on the basis of the frequency of keywords. However, this paper deals with the suspicious pattern on the basis of the frequency of keywords.