A study on the centrality measures to determine social media influencers of food-beverage products on Twitter

Abstract

This research aims to study and identify the Social Media Influencers (SMIs) in the Twitter community in Pizza Hut Industry. In social network analysis (SNA), Eigenvector Centrality (EC) will give the most influential node in a network. A node with the highest eigenvector value among the other nodes is the most influential/important node in a network. Data was collected from Twitter using the Twitter API with the hashtag #pizzahut. It applied the eigenvector centrality to observe the effect of the centrality value for Twitter data. The result shows that there is a significant difference between the three most influential users. This result will be used for future research that will be focused on small and medium enterprise (SME) Twitter data. This research is held a comparison analysis between the four centrality measurements approach: Degree Centrality, Betweenness Centrality, Closeness Centrality, and Eigenvector Centrality. for determining the most influential user with the social network Twitter as its case study.