Heterogeneous characters modeling of instant message services users' online behavior

• Published in: PloS one Vol. 13; no. 5; p. e0195518
• Main Authors: Cui, Hongyan, Li, Ruibing, Fang, Yajun, Horn, Berthold, Welsch, Roy E
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07-05-2018; Public Library of Science (PLoS)
• Subjects: Analysis; Artificial intelligence; Biology and Life Sciences; Cities; Communication; Communications networks; Computer and Information Sciences; Computer science; Consecutive events; Economic development; Engineering and Technology; Human behavior; Information dissemination; Instant messaging software; Instant messaging systems; Internet; Intervals; Laboratories; Medical treatment; Physical Sciences; Physics; Power law; Probability distribution functions; Research and Analysis Methods; Researchers; Social network analysis; Social networks; Social Sciences; Statistical mechanics; User behavior; China; Beijing China; United States > US; Massachusetts
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0195518

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.