Application of k-means clustering algorithm in sina microblog

Abstract

Opinion leaders play an important role in social network, and have a significant impact on the people around them. Although a lot of work have been made to identify opinion leaders, the effective methods still need to be developed, especially for the internet users like sina weibo. Sina Weibo is the largest and most popular online social network in china. It has a big influence on people's lives. In this paper, k-means clustering algorithm, a machine learning method, is used to find the opinion leaders from sina microblog social network. Preliminary test results show that this method is effective. What's more, the paper also analyzes the effect of opinion leaders in the sina microblog network structure.