Publications

Due to the spread of technology and world wide web, online social media has invaded every home in the world; hence, the analysis of such networks is considered an important yet challenging case of study for researchers. One of the most interesting fields of study in social network analysis is identifying influential users who are important actors in online social networks by having an impact on others. This work investigates the problem of identifying influential users on Twitter. Since Twitter is a user-friendly interactive platform, it is now an apparent competitor to other social medias as far as user interaction. Twitter is browsed by a variety of users, the most important are the most influential ones among them all. In order to identify influential users, a data set is collected between December 2015 and March 2016 reflecting real tweets from the top trendy hashtags on Twitter. In this paper, different measures are used such as influence measures, centrality measures and activity measures. In addition, association learning has been used to detect relationships between users. After identifying the influential users from association learning, these influential users are compared to the results of the abovementioned measures. The results of this study indicate that identifying influential users from association learning and validating these identified users with the results of influence measures is an effective method for detecting the influence of users on online social networks.