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Characterizing and modeling the dynamics of cyber movements

The availability of data from online social media has recently created unprecedented opportunities to explore human and social phenomena on a global scale. In this paper, we provide a quantitive, large scale, temporal analysis of the dynamics of online collective behavior in a specific cyber movement on Tianyacn, and point out that particle swarm theory can be used to model and simulate the variable interactions between cyber movement participants. This model updates each participant's position in accordance with two factors: historical experience accumulation and social interaction, and highlighting their importance in driving the dynamics of cyber movements.