Copyright © 2012 Yunpeng Xiao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The increasing development of social networks provides a unique source
for analyzing human dynamics in the modern age. In this paper, we analyze
the top-one Internet forum in China (“Tianya Club”) and identify the statistical properties of hotspots, which can promptly reflect the crowd events
in people's real-life. Empirical observations indicate that the interhotspot
distribution follows a power law. To further understand the mechanism of
such dynamic phenomena, we propose a hybrid human dynamic model that
combines “memory” of individual and “interaction” among people. To build
a rich simulation and evaluate this hybrid model, we apply three different
network datasets (i.e., WS network, BA network, and Karate-Club). Our
simulation results are consistent with the empirical studies, which indicate
that the model can provide a good understanding of the dynamic mechanism
of crowd events using such social networking data. We additionally analyze
the sensitivity of model parameters and find the optimal model settings.