@article{WuZhouXiaoetal.2010,
  author    = {Wu, Ye Wu and Zhou, Changsong and Xiao, Jinghua and Kurths, J{\"u}rgen and Schellnhuber, Hans Joachim},
  title     = {Evidence for a bimodal distribution in human communication},
  issn      = {0027-8424},
  doi       = {10.1073/pnas.1013140107},
  year      = {2010},
  abstract  = {Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.},
  language  = {en}
}
@article{WuZhouChenetal.2010,
  author    = {Wu, Ye and Zhou, Changsong and Chen, Maoyin and Xiao, Jinghua and Kurths, J{\"u}rgen},
  title     = {Human comment dynamics in on-line social systems},
  issn      = {0378-4371},
  doi       = {10.1016/j.physa.2010.08.049},
  year      = {2010},
  abstract  = {Human comment is studied using data from 'tianya' which is one of the most popular on-line social systems in China. We found that the time interval between two consecutive comments on the same topic, called inter-event time, follows a power-law distribution. This result shows that there is no characteristic decay time on a topic. It allows for very long periods without comments that separate bursts of intensive comments. Furthermore, the frequency of a different ID commenting on a topic also follows a power-law distribution. It indicates that there are some "hubs" in the topic who lead the direction of the public opinion. Based on the personal comments habit, a model is introduced to explain these phenomena. The numerical simulations of the model fit well with the empirical results. Our findings are helpful for discovering regular patterns of human behavior in on-line society and the evolution of the public opinion on the virtual as well as real society.},
  language  = {en}
}