Stationarity of the inter-event power-law distributions

Abstract

A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of these processes generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon are not yet clearly understood. In the present work we use the freely available Wikipedia editing records to unravel some features of this phenomenon. We show that even though the probability to start editing is conditioned by the circadian 24 hour cycle, the conditional probability for the time interval between successive edits at a given time of the day is independent from the latter. We confirm our findings with the activity of posting on the social network Twitter. Our result suggests there is an intrinsic humankind scheduling pattern: after overcoming the encumbrance to start an activity, there is a robust distribution of new related actions, which does not depend on the time of day.

5 figures. arXiv admin note: text overlap with arXiv:1601.00864

References in corpus (5)

• Dynamics of person-to-person interactions from distributed RFID sensor networks
• A Poissonian explanation for heavy-tails in e-mail communication
• On Universality in Human Correspondence Activity
• TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics
• Scaling in the Inter-Event Time of Random and Seasonal Systems

Cited by in corpus (5)

• SIS Epidemic Modelling on Homogeneous Networked System: General Recovering Process and Mean-Field Perspective
• Temporal scaling theory for bursty time series with clusters of arbitrarily many events
• Individual-driven versus interaction-driven burstiness in human dynamics: The case of Wikipedia edit history
• Hierarchical organization of bursty trains in event sequences
• Ising Model with Power Law Resetting