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Mining periodic patterns and cascading bursts phenomenon in individual e-mail communication

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  • Chenlong Li
  • Zhanjie Song
  • Wenjun Wang
  • Xu (Sunny) Wang

Abstract

Quantitative understanding of human activity is very important as many social and economic trends are driven by human actions. We propose a novel stochastic process, the Multi-state Markov Cascading Non-homogeneous Poisson Process (M2CNPP), to analyze human e-mail communication involving both periodic patterns and bursts phenomenon. The model parameters are estimated using the Generalized Expectation Maximization (GEM) algorithm while the hidden states are treated as missing values. The empirical results demonstrate that the proposed model adequately captures the major temporal cascading features as well as the periodic patterns in e-mail communication.

Suggested Citation

  • Chenlong Li & Zhanjie Song & Wenjun Wang & Xu (Sunny) Wang, 2019. "Mining periodic patterns and cascading bursts phenomenon in individual e-mail communication," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(14), pages 2603-2626, October.
  • Handle: RePEc:taf:japsta:v:46:y:2019:i:14:p:2603-2626
    DOI: 10.1080/02664763.2019.1605340
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