Poissonian bursts in e-mail correspondence

Abstract

Recent work has shown that the distribution of inter-event times for e-mail communication exhibits a heavy tail which is statistically consistent with a cascading Poisson process. In this work we extend the analysis to higher-order statistics, using the Fano and Allan factors to quantify the extent to which the empirical data depart from the known correlations of Poissonian statistics. The analysis shows that the higher-order statistics from the empirical data is indistinguishable from that of randomly reordered time series, thus demonstrating that e-mail correspondence is no more bursty or correlated than a Poisson process. Furthermore synthetic data sets generated by a cascading Poisson process replicate the burstiness and correlations observed in the empirical data. Finally, a simple rescaling analysis using the best-estimate rate of activity, confirms that the empirically observed correlations arise from a non-homogeneus Poisson process.

References in corpus (4)

• A Poissonian explanation for heavy-tails in e-mail communication
• On Universality in Human Correspondence Activity
• Impact of memory on human dynamics
• Unraveling the fluctuations of animal motor activity

Cited by in corpus (11)

• Circadian pattern and burstiness in mobile phone communication
• Bursty Human Dynamics
• Correlated dynamics in egocentric communication networks
• Hidden scaling patterns and universality in written communication
• On exact time-averages of a massive Poisson particle
• Stationarity of the inter-event power-law distributions
• Seeking for a fingerprint: analysis of point processes in actigraphy recording
• Fluctuation in e-mail sizes weakens power-law correlations in e-mail flow
• Computational Human Dynamics
• Study of the Power-Law Fluctuations in the Email Size
• Universal features of correlated bursty behaviour