Abstract
Research on temporal characteristics of human dynamics has attracted much attentions for its contribution to various areas such as communication, medical treatment, finance, etc. Existing studies show that the time intervals between two consecutive events present different non-Poisson characteristics, such as power-law, Pareto, bimodal distribution of power-law, exponential distribution, piecewise power-law, et al. With the occurrences of new services, new types of distributions may arise. In this paper, we study the distributions of the time intervals between two consecutive visits to QQ and WeChat service, the top two popular instant messaging services in China, and present a new finding that when the value of statistical unit T is set to 0.001s, the inter-event time distribution follows a piecewise distribution of exponential and power-law, indicating the heterogeneous character of IM services users’ online behavior in different time scales. We infer that the heterogeneous character is related to the communication mechanism of IM and the habits of users. Then we develop a combination model of exponential model and interest model to characterize the heterogeneity. Furthermore, we find that the exponent of the inter-event time distribution of the same service is different in two cities, which is correlated with the popularity of the services. Our research is useful for the application of information diffusion, prediction of economic development of cities, and so on.
Highlights
The study of distribution characteristics of human behavior has a long history
We focus on analyzing the temporal characteristics of QQ and WeChat users’ online behavior in two developed cities Chongqing(City-A) and Tianjin(City-B) in
This paper investigates the inter-event time distribution of QQ and WeChat in two cities, and reveals that the inter-event time distributions of QQ and WeChat in both cities follow a piecewise distribution of exponential and power-law distribution when the T is set to 0.001s, indicating that the online behavior of IM services users’ are heterogeneous in different time scales
Summary
The study of distribution characteristics of human behavior has a long history. For a long while, people have been using the Poisson distribution to quantify the model of human activities. Alexei Vazquez, et al In paper [3] find the distribution of inter-event times (IETs) between two consecutive human activities exhibits a heavy-tailed decay behavior and the oscillating pattern with a one-day period, reflective of the circadian pattern of human life. With the emergence of new services, human behavior may show some different temporal characteristics and need to be described with new types of distributions. The analysis of the temporal characteristics of QQ and WeChat users’ online behavior is useful for research on human dynamics. We focus on analyzing the temporal characteristics of QQ and WeChat users’ online behavior in two developed cities Chongqing(City-A) and Tianjin(City-B) in. We count the inter-event time distribution as follows: 1. It’s worth looking in more detail at the distributions when T is set to 0.001s
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