Research on the Human Dynamics in Mobile Communities Based on Social Identity

Through analyzing the data about the releases, comment, and forwarding of 120,000 microblog messages in a year, this paper finds out that the intervals between information releases and comment follow a power law; besides, the analysis of data in each 24 hours reveals obvious differences between microblogging and website visit, email, instant communication, and the use of mobile phone, reflecting how people use fragments of time via mobile internet technology. The paper points out the significant influence of the user's activity on the intervals of information releases and thus demonstrates a positive correlation between the activity and the power exponent. The paper also points out that user's activity is influenced by social identity in a positive way. The simulation results based on the social identity mechanism fit well with the actual data, which indicates that this mechanism is a reasonable way to explain people's behavior in the mobile Internet.

[1]  Jinghua Xiao,et al.  Human comment dynamics in on-line social systems , 2010 .

[2]  Bruno Gonçalves,et al.  Human dynamics revealed through Web analytics , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  M. Marsili,et al.  Optimization in task-completion networks , 2007, 0712.3906.

[4]  Zengru Di,et al.  Analyzing netizens' view and reply behaviors on the forum , 2009, 0908.4388.

[5]  Wang Bing-Hong,et al.  Interest-Driven Model for Human Dynamics , 2010 .

[6]  G. Madey,et al.  Uncovering individual and collective human dynamics from mobile phone records , 2007, 0710.2939.

[7]  Hai-Bo Hu,et al.  Empirical analysis of individual popularity and activity on an online music service system , 2008 .

[8]  Tao Zhou,et al.  Empirical analysis on temporal statistics of human correspondence patterns , 2008 .

[9]  Andrzej Grabowski,et al.  EXPERIMENTAL STUDY OF THE STRUCTURE OF A SOCIAL NETWORK AND HUMAN DYNAMICS IN A VIRTUAL SOCIETY , 2007 .

[10]  J. G. Oliveira,et al.  Human Dynamics: The Correspondence Patterns of Darwin and Einstein , 2005 .

[11]  Tao Zhou,et al.  Modeling human dynamics with adaptive interest , 2007, 0711.0741.

[12]  Ph Blanchard,et al.  Modeling human activity in the spirit of Barabasi's queueing systems. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Anna Chmiel,et al.  Scaling of human behavior during portal browsing. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Zhi-Dan Zhao,et al.  Empirical Analysis on the Human Dynamics of a Large-Scale Short Message Communication System , 2011 .

[15]  Beom Jun Kim,et al.  Role of activity in human dynamics , 2007, EPL (Europhysics Letters).

[16]  Wang Bing-Hong,et al.  Heavy-Tailed Statistics in Short-Message Communication , 2009 .

[17]  Alexei Vazquez.  Impact of memory on human dynamics , 2007 .

[18]  Filippo Radicchi.  Human Activity in the Web , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  A. Barabasi,et al.  Human dynamics: Darwin and Einstein correspondence patterns , 2005, Nature.

[20]  Peng Wang,et al.  Heterogenous scaling in interevent time of on-line bookmarking , 2010, ArXiv.

[21]  Jin-Li Guo,et al.  Empirical study and modeling of human behaviour dynamics of comments on Blog posts , 2010, ArXiv.

[22]  Albert-László Barabási,et al.  The origin of bursts and heavy tails in human dynamics , 2005, Nature.

[23]  Jürgen Kurths,et al.  Evidence for a bimodal distribution in human communication , 2010, Proceedings of the National Academy of Sciences.

[24]  Zhi-Qiang Jiang,et al.  Online-offline activities and game-playing behaviors of avatars in a massive multiplayer online role-playing game , 2009, ArXiv.

[25]  Albert-László Barabási,et al.  Modeling bursts and heavy tails in human dynamics , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.