Developing a model for analyzing users’ behavior in social networks (The Case of Twitter)

Today, with the advent of cyberspace and the expansion of social networks, users have a wide range of activities in social networks that the importance of issues and their impacts on users have led to extensive analysis in this area, so that this emerging field could be used to improve services to users. In social networks, people are influenced by other users, and this has led the researcher to identify influential users in Twitter, to extract the model for user behavior. Influential users in certain topics spread the behavior and influence the thoughts and ideas of other users. In this study, to find effective users, various types of Twitter network relationships have been used to analyze the network. Based on the indicators of social network analysis, user interactions have been studied and the coefficient of each relationship model has been obtained by performing various experiments. In the next step, the order of each relationship model in determining the effective user in Twitter is specified. The results showed that among the four types of interaction, including retweet, pointing, responding and following to form a communication graph, according to the conducted studies, the effect of retweeting is more than pointing and responding and the effect of following relationship was less than other relationships.