Publications

Online Social Networks invaded every home in the world and thus the analysis of such networks became a challenging case of study. Identifying influential users on online social networks is one of the most interesting fields of study in social network analysis. These users might have impact on other users on a network yielding a change in the whole network graph. This paper studies the problem of identifying influential users on some trendy hashtags on Twitter. In order to identify these influential users, data reflecting real tweets from the top trendy hashtags on Twitter have been collected between December 2015 and March 2016. In this paper, Association Rule Learning has been employed to identify influential users in these trendy hashtags. Moreover, these identified influential users were ranked based on different Influence Measures in order to study the effect of these measures on studying the evolution of the hashtags. The results of this study indicate the effectiveness of identifying influential users using Association Rule Learning and identifying the most effective Influence Measures.