![]() | Only 14 pages are availabe for public view |
Abstract The massive amount of data generated form OSN created a persistent need to different types of analysis. Accordingly, the researcher decided in this research to benefit from the social and activity data on OSN in order to identify the Social Media Influencers (SMI). The research proposed a new framework that helps in solving the issue regarding the process of influencers’ identification. The proposed framework consists of two parts. The first is a proposed metric to identify influencers in OSN. The second part is an analysis to define the characteristics of the top ranked influencers. In this research, the researcher depends on a sample data gathered from twitter in order to apply the proposed metric. The proposed metric results in a set of users identified as influencers in comparison to other sets identified by metrics in the literature. Besides, some characteristics were determined and help in distinguishing influencers from non-influencers |