ABSTRACT

In this study, we considered the issue of determination of the most effective user in the twitter online social network. We worked on asocial network graph which have relationships (edges) between users who posteda tweet and other users who re-posted it. In other words, we assume that there is a relationship between User-X and User-Y when User-X posted a tweet and User-Y re-postedit. In Social Network Analysis (SNA), there are four fundamental centrality measures such as Degree Centrality, Closeness Centrality, Betweenness Centrality, and Eigenvector Centralities.We developed a new approach for determiningthe most effective user in Twitter online social network by using an index named E-User (Effective User) Index.Through this index, we think that we are able to obtain more realistic results in SNA for Twitter.We designed a small weighted and directed social network graph by using a simulated data and used it for determining the most effective user in this study. In our graph, weights indicate the number of retweets between a user and other user, and directions indicate which user did retweet to other user’s tweet. In the graph, directions can be bidirected. This means that both users did retweet their tweets to each other.