Novel user influence measurement based on user interaction in microblog

Abstract

With the development of science and technology, various social networks have emerged in recent years and microblog is a prevailing one. This paper focuses on how to identify the most influential users quantitatively in microblog and proposes a new ranking method which employs the fact that a follower's contribution to the influences of his/her followees varies and depends greatly on the interactions between them. We consider bidirectional interactions from perspectives of followees and followers, and measure the interactive degree by four factors comprised of retweeting strength, commenting intensity, mentioning density and a special indicator to the potential interactions called keyword similarity. The experimental results show that our method based on user interaction is better in calculating the user influence.