Behavior statistics and social network analysis of online Go game players

The statistics and principle of human behavior are of great importance in interpreting the origin and formation of human behavior in many scopes including economics, sociology, biology and engineering systems. As a basic step toward the understanding of Go Players' behavior, we investigate several statistical properties, including the distribution of total game number in different time scale, the match intensity in one day and the lifetime distribution of typical online users, based on large amount of Go game data from amateur online Go platform. In addition, the social network analysis verifies that the degree distribution of such network users also follows power-law principle although its slope is much smaller than reported network data set. Our findings and analysis reveals some fundamental features for online game players, which should be vital for understanding the human dynamics in other fields.