Abstract
By exploiting the statistical analysis method, human dynamics provides new insights to the research of human behavior. In this paper, we analyze the characteristics of the computer operating behavior through a modified multiscale entropy algorithm with both the interval time series and the number series of individuals’ operating behavior been investigated. We also discuss the activity of individuals’ behavior from the three groups denoted as the retiree group, the student group and the worker group based on the nature of their jobs. We find that the operating behavior of the retiree group exhibits more complex dynamics than the other two groups and further present a reasonable explanation for this phenomenon. Our findings offer new insights for the further understanding of individual behavior at different time scales.
Highlights
The concept of human dynamics [1,2] has attracted increasing research interest since it was first proposed in 2005
With both the interval time series and the operation-number series of the individuals taken into account, we apply the modified MSE (MMSE) analysis to quantify the dynamical complexity of individual behavior for the three groups
We should mention that the MMSE algorithm is less affected by the sequence length than the Multiscale Entropy (MSE) algorithm, it still provides an inaccurate estimation when the length of time series is less than 500
Summary
The concept of human dynamics [1,2] has attracted increasing research interest since it was first proposed in 2005. The coarse-gained procedure results in a short time series which lead to imprecise estimation of sample entropy or even undefined entropy values [15,16] To overcome this drawback, Wu et al [17] proposed the modified MSE (MMSE) algorithm in which a moving-averaged procedure replace the coarse-gained procedure and a time delay is introduced to acquire a more accurate estimation of sample entropy. Individuals of the three groups denoted as the retiree group, the student group and the worker group, are selected randomly from the original dataset based on the nature of their jobs With both the interval time series and the operation-number series of the individuals taken into account, we apply the MMSE analysis to quantify the dynamical complexity of individual behavior for the three groups.
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