Modeling bursts and heavy tails in human dynamics
Harvard University · University of Notre Dame · +3 more institutions
Abstract
The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of…
Citation impact
- FWCI
- 103.04
- Percentile
- 100%
- References
- 78
Authors
6- AVAlexei VázquezCorresponding
Harvard University, University of Notre Dame, Dana-Farber Cancer Institute
- JGJ. G. Oliveira
University of Notre Dame, University of Aveiro
- ZDZoltán Dezső
University of Notre Dame
- KGK.-I. Goh
University of Notre Dame, Harvard University, Dana-Farber Cancer Institute
- IKImre Kondor
Collegium Budapest
Topics & keywords
- Poisson distribution
- Human dynamics
- Queueing theory
- Computer science
- Queue
- Heavy-tailed distribution
- Process (computing)
- Dynamics (music)
- Peace, Justice and strong institutions