Abstract
The quantitative analysis of human pattern is an effective way to understand the complex social system. Relevant empirical studies reveal that human behavior in time follow a power-law distribution rather than a Poisson distribution. This paper aims at conducting statistical analyses based on the records of Qzone posts and interactive messages. The results show that the inter-event time distribution of posts and interaction follows a power-law distribution. Additionally, the time intervals of post comments differ from the time intervals of interact and in that there exists a clear cut-off point in the distribution of posting time, which indicates the subjection to a two-stage power-law. At the individual level, the posting time distribution exhibits fat tails. The analysis of post behavior indicates that there is a monotonous and negative relationship between the activity level and power-law exponent. The characteristics of local peaks also illustrate the burstiness and memory of post behavior.
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References
Barabasi, A.-L.: The origin of bursts and heavy tails in human dynamics. Nature 435(7039), 207–211 (2005)
Onnela, J.-P., et al.: Structure and tie strengths in mobile communication networks. Proceedings of the National Academy of Sciences 104(18), 7332–7336 (2007)
Song, C., et al.: Limits of predictability in human mobility. Science 327(5968), 1018–1021 (2010)
Anteneodo, C., Dean Malmgren, R., Chialvo, D.R.: Poissonian bursts in e-mail correspondence. The European Physical Journal B-Condensed Matter and Complex Systems 75(3), 389–394 (2010)
Wuchty, S., Uzzi, B.: Human communication dynamics in digital footsteps: a study of the agreement between self-reported ties and email networks. PloS one 6(11), e26972 (2011)
Chun, H., et al.: Comparison of online social relations in volume vs interaction: a case study of cyworld. In: Proceedings of the 8th ACM SIGCOMM Conference on Internet Measurement. ACM (2008)
Xue-Zao, R., et al.: Mandelbrot Law of Evolving Networks. Chinese Physics Letters 29(3), 038–904 (2012)
Song, Y., Chuang Z., Wu, M.: The study of human behavior dynamics based on blogosphere. In: 2010 International Conference on Web Information Systems and Mining (WISM), vol. 1. IEEE (2010)
Chen, G., Han, X., Wang, B.: Multi-level scaling properties of instant-message communications. Physics Procedia 3(5), 1897–1905 (2010)
Milojević, S.: Power law distributions in information science: Making the case for logarithmic binning. Journal of the American Society for Information Science and Technology 61(12), 2417–2425 (2010)
Zhi-Dan, Z., et al.: Empirical analysis on the human dynamics of a large-scale short message communication system. Chinese Physics Letters 28(6), 068901 (2011)
Zhou, T., et al.: Role of activity in human dynamics. EPL (Europhysics Letters) 82(2), 28002 (2008)
Wei, H., et al.: Heavy-tailed statistics in short-message communication. Chinese Physics Letters 26(2), 028–902 (2009)
Wang, P., et al.: Heterogenous scaling in the inter-event time of on-line bookmarking. Physica A: Statistical Mechanics and its Applications 390(12), 2395–2400 (2011)
Dezsö, Z., et al.: Dynamics of information access on the web. Physical Review E 73(6), 066132 (2006)
Livina, V.N., Havlin, S., Bunde, A.: Memory in the occurrence of earthquakes. Physical review letters 95(20), 208–501 (2005)
Harder, U., Paczuski, M.: Correlated dynamics in human printing behavior. Physica A: Statistical Mechanics and its Applications 361(1), 329–336 (2006)
Goh, K.-I., Barabási, A.-L.: Burstiness and memory in complex systems. EPL (Europhysics Letters) 81(4), 48002 (2008)
Cai, S.-M., et al.: Scaling and memory in recurrence intervals of Internet traffic. EPL (Europhysics Letters) 87(6), 68001 (2009)
Vázquez, A., et al.: Modeling bursts and heavy tails in human dynamics. Physical Review E 73(3), 036–127 (2006)
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Li, B., Hu, N., Wang, W., Yuan, N. (2015). Temporal Pattern of Human Post and Interaction Behavior in Qzone. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9141. Springer, Cham. https://doi.org/10.1007/978-3-319-20472-7_6
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DOI: https://doi.org/10.1007/978-3-319-20472-7_6
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