Increasing the information content of social network groups and clients using Social Mining

Abstract

Connections, contacts, and commerce on social networks are expanding dynamically and have become attractive to many visitors who enjoy, for example, predicting events in a group, finding a person, finding out necessary information about him. Intelligent systems for activating the client, the client base, increasing information content from them began to be actively studied, taking into account the processes occurring in social networks. New forms of feedback, mechanisms (regulators) are activated; their new systemic and synergistic effects are being investigated. The problems of the traditional and the tasks of modern (media network) sociology, social network technology, the methodology of research on society are investigated in the work on the basis of the principles of system dynamics. Hierarchical client structures in which the client, the cluster has its own weight, rank, are considered. The important task of identifying the rank and client, for example, the initiator (coordinator) of network processes, is investigated. A graph model of such hierarchical structures, taking into account hierarchical subordination, and the measures of connectivity necessary in assessing the evolutionary potential of social network groups, is proposed. The procedure for assessing the potential of a network (group) is given. The results are the application of Social Mining in