Double dynamic scaling in human communication dynamics

Shengfeng Wang, Xin Feng, Ye Wu and Jinhua Xiao

Physica A: Statistical Mechanics and its Applications, 2017, vol. 473, issue C, 313-318

Abstract: In the last decades, human behavior has been deeply understanding owing to the huge quantities data of human behavior available for study. The main finding in human dynamics shows that temporal processes consist of high-activity bursty intervals alternating with long low-activity periods. A model, assuming the initiator of bursty follow a Poisson process, is widely used in the modeling of human behavior. Here, we provide further evidence for the hypothesis that different bursty intervals are independent. Furthermore, we introduce a special threshold to quantitatively distinguish the time scales of complex dynamics based on the hypothesis. Our results suggest that human communication behavior is a composite process of double dynamics with midrange memory length. The method for calculating memory length would enhance the performance of many sequence-dependent systems, such as server operation and topic identification.

Keywords: Communication pattern; Memory length; Heavy tail (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:473:y:2017:i:c:p:313-318

DOI: 10.1016/j.physa.2017.01.010

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