Applying the Approach Based on Several Social Network Analysis Metrics to Identify Influential Users of a Brand

Abstract

Online social networks, have become an integral part of our daily lives. People widely share their views on various topics and feelings with other users on these platforms. Due to the formation of extensive relationships between users, researchers seek communities on online social networks to achieve their goals. But discovering the structure of the communities in these networks has not been enough from the e-commerce point of view, so the problem of finding influencers became apparent. In this article, a case study was conducted on the Zar Macaron brand. To do this different approaches for identifying influential users were compared, and we also created two crawlers to collect data from Instagram. In the analysis phase, we have used Gephi as a tool to identify communities and influential users. Many social network analysis metrics have been applied to the dataset to achieve reasonable results. Moreover, time analysis has been conducted to discover the hidden patterns of activity within the network to validate previous results. Our findings show that applying data analysis techniques to users' online behavior is a powerful tool for predicting user impact levels. Finally, we confirmed our results by observing objective facts.