Identifying trusted similar users using stochastic model and next-closure based knowledge model in online social networks

The social network is a medium where people of different religions, races, languages, hobbies, etc. come together and exchange information and knowledge without any social restrictions. Though they are divergent in many areas of their existence, they are all brought together by their interests. They tend to have closer communication only with those who have similar interests and trust. So identifying users of similar interest and evaluating their trustworthiness is mandatory in an online social network (OSN). As the user behavior in social network is dynamic, the stochastic process which evolves the randomness over the period is employed to compute the closeness between users in OSN. The current work proposes to identify the similar interested groups, based on the knowledge-based model through the provenance factors using formal concept analysis (FCA) and Jaccard index. The probability of closeness is derived using stochastic process reflecting the trustability of the user with respect to the different type of interaction behavior such as like, comment and chat.