A link analysis model based on online social networks

Abstract

As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. Traditional on-line social network researches are based a certain comment interaction. Though some interest conclusions have been obtained, the understanding of the entire on-line social network is one-sided. In this paper, we compare four different types of networks proposed by previous researchers. Statistical analysis reveals that those four networks are consistent in nature (both the "small-world effect" and skewed degree distributions are found in them). To discover the mechanism behind these network observations, we propose a single-factor model with a single parameter K; using this model, various networks can be obtained when we change the parameter K in a given range. Simulation experiment based on this model show that the simulation results and the real data are consistent, which means that our model is valid. © 2011 Springer-Verlag.