This paper studies the human behavior in the top-one social network system in China (Sina Microblog system). By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time) obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network. 1. Introduction The increasing development of social network provides a unique source for analyzing human dynamics in the modern age. With the evolution of the mobile communication technology, people can enjoy various social applications more conveniently, such as Twitter and especially Facebook. Application development is a direct result of data surge, and the era of big data and complex system give us an unprecedented opportunity to study human behavior [1]. In China, Sina Microblog (http://en.wikipedia.org/wiki/Sina_Weibo), which is akin to a hybrid of Twitter and Facebook, is the most popular social network sites for information propagation and discussion among people. Up to May 2012, Sina Microblog has more than 300 million registered users and generates more than 100 million microblogs every day. It occupies 57% of the microblog users, as well as 87% of the microblog activities in China. There are 60% of active users who log in through the mobile terminal (http://tech.sina.com.cn/i/2012-05-15/12307109653.shtml.) Such systems have tons of information, not only from the perspective of individual behaviors but also in terms of human interactions. Therefore, such social network sites provide great potential to analyze human behaviors in social network for understanding human dynamics. The study of complex systems also attracts researchers in various fields [2–7]. In traditional studies on human behaviors, human behavior is usually assumed as
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