Social network analysis using big data

Abstract

The increasing use of social networks, such as Facebook, Twitter, and Weibo, has produced and is producing huge volume of data. Business firms and other organizations are interested in discovering new business insight to increase business performance. By using advanced analytics, enterprises can analyze big data to learn about relationships underlying social networks that characterize the social behavior of individuals and groups. Using data describing the relationships, we are able to identify social leaders who influence the behavior of others in the network, and on the other hand, to determine which people are most affected by other network participants. This study focuses on modeling the knowledge diffusion in social networks. We will present a new evolving model of a directed, scale-free network. We will test the effectiveness of our model by a simulation using data of a real-world social network.