Analysis of human behavior statistics law based on WeChat Moment

WeChat is one of the most popular social platforms where users share their feelings and opinions in Moments, Wechat postings that are usually in forms of text, pictures and videos, etc. This paper analyze the Moment posting behavior of WeChat users by obtaining 10196 Moments of 628 users. According to the result, both the number of commits and the inter-event time conform to the power-law distribution in a continuous period of time, revealing a fact that the majority of Moments are posted by a small portion of users. Then our study on individual activity unveils a relatively strong positive correlation between user activity and the exponent of inter-event time distribution, which agrees with previous studies. Additionally, the paper points out that WeChat users have a low-burstiness, low-memory posting pattern, which is slightly different from that of other online systems owing to Wechat users’ generally high activity. This paper also studied the effects of sleep on user behavior. Our findings have significance in understanding the human dynamic mechanism of Wechat users. •Distributions of both commit number and inter-event time fit power-law form.•WeChat user is of weak burstiness and weak memory as a whole.•The fitted value increases more slowly when the activity level increases.•WeChat user with higher activity level appears a relatively lower burstiness.