On Identification of Organizational and Individual Users Based on Social Content Measurements

Social network user identification is of great value and significance for predicting users' behavior, analyzing and regulating social networks, and studying the interaction between users. This paper studies the identities of social network users, divides them into organizational and individual users in terms of their identities, and explicitly defines and identifies both types of users. This paper also distinguishes a user as an organization or an individual according to the contents of text, multimedia, and their time series published in a social network. During the identification, the content (topic) complexity and normalization of the user in text content are measured; the picture features and time-series content of the user are being analyzed, and the machine-operable method that identifies a user as an organization or an individual is proposed from different perspectives so as to perform this identification. Finally, in order to verify the feasibility and effectiveness of the identification method proposed in this paper, an experiment was made to the data collected from Sina Weibo and the probability model identification method was used to make a comparative analysis. Results indicate that the identification method used in this paper can effectively distinguish between a user as an organization or an individual.