A stochastic evolutionary model for capturing human dynamics. (19th August 2015)

• Record Type: Journal Article
• Authors: Fenner, Trevor; Levene, Mark; Loizou, George
• Is Part Of: Journal of statistical mechanics. (2015:Aug.)
• Publication Date: 2015-08-19
• Subjects: 12; 12/020 -- 12/110; Statistical mechanics -- Periodicals; Mechanics -- Statistical methods -- Periodicals; 530.1305
• DOI: 10.1088/1742-5468/2015/08/P08015
• Languages: English
• ISSNs: 1742-5468

Abstract

Abstract: The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in various contexts. Here we propose a generative model to capture the dynamics of survival analysis, traditionally employed in clinical trials and reliability analysis in engineering. We derive a general solution for the model in the form of a product, and then a continuous approximation to the solution via the renewal equation describing age-structured population dynamics. This enables us to model a wide rage of survival distributions, according to the choice of the mortality distribution. We provide empirical evidence for the validity of the model from a longitudinal data set of popular search engine queries over 114 months, showing that the survival function of these queries is closely matched by the solution for our model with power-law mortality.