Diversity Leads to Accelerating Growth in Online Social Systems
Lingfei Wu, Jiang Zhang, Jonathan J. H. Zhu, Kai Lei, Qian Mo · 2011
Research on the growth of online social systems not only is interesting in its own right, but also yields insights for website management and web crawling. Traditional models that describing the growth of online systems can be divided between linear and nonlinear versions. Linear models, including the BA model, assume that the average activity of users in a system is a constant independent of system size. Hence the total activity is a linear function of the system size. On the contrary, nonlinear models suggest that the average activity is affected by the system size and the total activity is a nonlinear function of the system size. In the current study, we obtain supporting evidence for the nonlinear growth assumption from data on Internet users ’ file sharing and blogging behavior. We find that there is a power law relationship between the activity F and the system size P, which can be expressed as F ~ P � (��> 1). We call this pattern accelerating growth and analytically attribute it to time-variant diversity in individual activities. We also show that a greater diversity leads to a faster growth. Our findings of the relationship between diversity and growth rate is supported by empirical data and numerical simulations. 1.