[1T4-GS-4] Web intelligence

[1T4-GS-4-01] Analysis of web service usage patterns and habituation

〇Makoto Takeuchi^1,2, Yukie Sano¹ (1. University of Tsukuba, 2. CyberAgent, Inc.)

[[Online]]

Keywords:event time series, burstiness, power-law distribution, user behavior model

It is known that individual behavior patterns are heterogeneous temporally with regard to various types of human behavior. The distributions of Inter-Event Times (IET) of such event time series show a long-tail distribution like a power-law distribution. In particular, it has been reported that there are individual differences in the shape of the IET distributions of physical action event time series (e.g., arm movements) and smartphone touch event time series, but what the differences in the IET distributions mean has not been clarified. We focused on the click event time series of Web services and confirmed that the statistical pattern including the IET distribution for each user changes over time. The results of our analysis suggest that this change in the statistical pattern can be interpreted as habituation to the operation of the Web service. Our results are important in that they provide insight into the origin of temporal heterogeneity common to various human behaviors. Furthermore, our results could be utilized for the improvement of the user experience of web services.