Identification of Query-Oriented Influential Users in Online Social Platform

In recent time, online social influencers are affecting perceptions and behaviors of their connections by becoming a medium of swaying opinions. As a result, influential user identification has become inevitable to analyze the dynamic evolution of Online Social Networks (OSNs) for any new strategy either for viral marketing applications or controlling the propagation of provoking information. Our objective is to detect the influential users on Twitter, an online social networking with a flow of remarkable interconnections. Our proposed method is to demonstrate influential users using a collection of tweets matching a specified query on multiple topics in different time period by applying temporal TwitterRank. We conduct this experiments on real dataset to denote the effectiveness and performance of the proposed method. The findings provide that an user can achieve great influence based on number of tweets in various time period and the number of followers. This result also suggests that one topological measure alone may reflect less about the influence of users and provide new insights for sociology and other concepts. According to the proposed method, the experimental result shows the dynamic rank of influential users across multiple topics and time.