Information Diffusion Model and Hadoop Implementation Research on Online Social Network

Abstract

Social networks are currently gotten increasing focus with the growth of online social network services, such as Facebook, Sina Weibo. One major challenge for social network research is how to build information diffusion model to describe the complex information diffusion model. For this purpose, information diffusion models are researched. To show the importance of network topology, how to identify the most important spreaders in the network is a key scientific problem. Different kinds of network centrality measure methods are analyzed. The role of a potential edge in social network is analyzed. The relationship between network topology structure and information diffusion dynamics model is analyzed. Pagerank algorithm for SinaWeibo users are implemented in Hadoop cloud computing platform. Experiment result shows that Pagerank algorithm can be implemented in Hadoop cloud platform to recognize the important spreaders in social network. Big data in social network can be analyzed in the platform.