Exploring gender based influencers using Social Network Analysis

The social network is dominating the society with interactive collaboration and social interactions. It is very common now to share, post, like and comment on various topic of interest. These interactions has given space for research to explore the social relationships among online users. Predicting the influencers in social network can help us to control the flow of information in them. The objective of this research work is to analyze the likes in Facebook users cover photos to identify the influencers and their gender. Using clustering coefficient, degree analysis and triadic census we were able to identify the influencers and found that men are strong influencers in the network.