Detecting Communities and Surveying the Most Influence of Online Users
نویسندگان
چکیده
Social network is a virtual environment that provides services for connecting users with the same interests, points of view, gender, space and time. Beside connection, information exchange, communication, entertainment and so on. Social network is also an environment for users who work in online business, advertisement or politics, criminal investigation. How to know what users discuss topics via exchanged contents and communities which users join in? In this paper, we propose a model by using topic model combined with K-means to detect communities of online users. Each user in social network is represented by a vector in which the components are the distribution probabilities of interested topics of that user. Based on the components of this vector, we discover the interested topics of online users to detect communities and survey users who are the most influence in communities to recommend for spreading information on social network.
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