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Empirical analysis on temporal statistics of human correspondence patterns

Author

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  • Li, Nan-Nan
  • Zhang, Ning
  • Zhou, Tao

Abstract

Recently, extensive empirical evidence shows that the timing of human behaviors obeys non-Possion statistics with heavy-tailed interevent time distribution. In this paper, we empirically study the correspondence pattern of a great Chinese scientist, named Hsue-Shen Tsien. Both the interevent time distribution and response time distributions deviate from the Poisson statistics, showing an approximate power-law decaying. The two power-law exponents are more or less the same (about 2.1), which strongly support the hypothesis in [A. Vázquez, J.G. Oliveira, Z. Dezsö, K.-I. Goh, I. Kondor, A.-L. Barabási, Phys. Rev. E 73 (2006) 036127] that the response time distribution of the tasks could in fact drive the interevent time distribution, and both the two distributions should decay with the same exponent. Our result is against the claim in [A. Vázquez, J.G. Oliveira, Z. Dezsö, K.-I. Goh, I. Kondor, A.-L. Barabási, Phys. Rev. E 73 (2006) 036127], which suggests the human correspondence pattern belongs to a universality class with exponent 1.5.

Suggested Citation

  • Li, Nan-Nan & Zhang, Ning & Zhou, Tao, 2008. "Empirical analysis on temporal statistics of human correspondence patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(25), pages 6391-6394.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:25:p:6391-6394
    DOI: 10.1016/j.physa.2008.07.021
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    Citations

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    Cited by:

    1. Cao, Shihao & Wang, Zhihua & Liu, Chengrui & Wu, Qiong & Li, Junxing & Ouyang, Xiangmin, 2023. "A novel solution for comprehensive competing failure process considering two-phase degradation and non-Poisson shock," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    2. Wang, Peng & Ma, Qiang, 2017. "From heavy-tailed to exponential distribution of interevent time in cellphone top-up behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 10-17.
    3. Wang, Qing & Guo, Jin-Li, 2010. "Human dynamics scaling characteristics for aerial inbound logistics operation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2127-2133.
    4. Yang, Tian & Feng, Xin & Wu, Ye & Wang, Shengfeng & Xiao, Jinghua, 2018. "Human dynamics in repurchase behavior based on comments mining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 563-569.
    5. Peng, Dan & Han, Xiao-Pu & Wei, Zong-Wen & Wang, Bing-Hong, 2015. "Punctuated equilibrium dynamics in human communications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 36-44.
    6. Nicolò Pagan & Wenjun Mei & Cheng Li & Florian Dörfler, 2021. "A meritocratic network formation model for the rise of social media influencers," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    7. Yu, Jiefei & Hu, Yanqing & Yu, Min & Di, Zengru, 2010. "Analyzing netizens’ view and reply behaviors on the forum," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3267-3273.
    8. Lin, Zhenquan & Meng, Fan, 2018. "Empirical analysis on the runners’ velocity distribution in city marathons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 533-541.
    9. Yan, Qiang & Wu, Lianren & Zheng, Lan, 2013. "Social network based microblog user behavior analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1712-1723.
    10. Wang, Shengfeng & Feng, Xin & Wu, Ye & Xiao, Jinhua, 2017. "Double dynamic scaling in human communication dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 313-318.

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