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

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.

KEYWORDS:

• Individual e-mail communication
• human dynamic modeling
• Markov cascading non-homogeneous poisson process

Acknowledgments

The authors thank Drs G. Kossinets and J.P. Eckmann for providing the data used in this research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is supported by National Natural Science Foundation of China [grant no. 91746107]; the State Scholarship Fund of China Scholarship Council (CSC); and National Science and Engineering Research Council of Canada.