Human behavior in online social systems

We present and study data concerning human behavior in four online social systems: (i) an Internet community of friends of over 10⁷ people, (ii) a music community website with over 10⁶ users, (iii) a gamers’ community server with over 5 × 10⁶ users and (iv) a booklovers’ website with over 2.5 × 10⁵ users. The purpose of those systems is different; however, their properties are very similar. We have found that the distribution of human activity (e.g., the sum of books read or songs played) has the form of a power law. Moreover, the relationship between human activity and time has a power-law form, too. We present a simple interest-driven model of the evolution of such systems which explains the emergence of two scaling regimes.