Finding Correlation Between Twitter Influence Metrics and Centrality Measures for Detection of Influential Users

Abstract

With such a great ease of sharing thoughts with the whole world and ever-increasing delightful features, social media such as Twitter has been influencing many aspects of our lives such as product recommendations, movie reviews, political campaigns, game predictions, and so on. It can be found that often few individuals tend to be influential enough to drive a whole group or network towards a particular thought. Network Centrality is one of the most widely studied and used concepts in social network analysis. There are other Twitter-specific measures known as influence metrics which are often used for social network analysis. The work presented in this paper reports on the implementation of some centrality measures and Twitter-specific influence measures are applied on a Twitter network of professional wrestling. The paper also reports on the correlation among the different measures for detecting influential users.