Statistical Physics of Social Network Systems: Transportation Passenger Flow and Twitter Dynamics

S. Goh, H. Kwon, K. Lee, and M.Y. Choi

Abstract

Social networks have recently attracted much attention, with attempts to understand social behavior with the aid of statistical mechanics of complex systems. Collective properties emerge from couplings between components, i.e., individual persons and transportation or communication nodes. As characteristic social network systems, we consider the mass transportation network and the Twitter network, and examine passenger flows in the Seoul transportation network and time evolution of tweeting. Observed are skew distributions and criticality manifested by power-law correlations. Such criticality is probed by means of the scaling and renormalization analysis of the modified gravity model applied to the system, which reveals the underlying structure. As for Twitter, we propose a good measure for the information-sharing tendency, and present a mathematical model for the Twitter dynamics. This allows to describe the time evolution of tweeting, based on the information-sharing tendency.