Empirical analysis of the evolution of follower network: A case study on Douban

Abstract

Follower networks such as Twitter and Digg are becoming popular form of social information networks. This paper seeks to gain insights into how they evolve and the relationship between their structure and their ability to spread information. By studying the Douban follower network, which is a popular online social network in China, we provide some evidences showing its suitability for information spreading. For example, it exhibits an unbalanced bow-tie structure with a large out-component, which indicates that the majority of users can spread information widely; the effective diameter of the strongly connected component is shrinking as the user base grows, which facilitates spreading; and the transitivity property shows that people in a follower network tend to shorten the path of information flow, i.e., it takes fewer hops to spread information. Also, we observe the following users' behaviors, a user's following activity decays exponentially during her lifetime and the following behaviors differ according to the age of the account. These findings provide a deep understanding on the evolution of follower networks, and can provide guidelines on how to build an efficient information diffusion system.