[目的/意义]相对于传统的信息行为分析，数据驱动的信息行为研究更注重数据的外在性与客观性，所得的结果能够更为全面地认识用户信息行为本质特征。[方法/过程]通过自行构建的APP实现对微信用户分享和阅读行为记录的采集，并对微信用户信息行为的时间特性进行系统的分析。[结果/结论]结果表明：微信用户日常信息行为存在显著的假日效应，但是在信息行为时间间隔分布上存在明显厚尾现象和很强的阵发性，预示着微信用户信息行为具有较高的复杂性和不确定性，无法对其产生过程实现有效的预测；此外，微信用户所分享的内容具有很强的时效性，多数内容在微信中能够得到及时的传播，但传播链长度显著受分享内容主题的影响。
[Purpose/significance] Compared with traditional information behavior approaches, the research on information behavior based on the data-driven approach pays more attention to the externality and objectivity of data, and the testing results can be more comprehensive understanding of user information behavior characteristics.[Method/process] This paper realizes the collection of Wechat users' sharing and reading behavior records through a self-built APP, and systematically analyses the temporal characteristics of Wechat users' information behavior.[Result/conclusion] The results show that the daily information behavior of Wechat users has significant holiday effect, but there are a obvious fat-tail phenomenon and strong burstiness effect in the time interval distribution of information behavior, which indicate that the information behavior of Wechat users has high complexity and uncertainty, and can not effectively predict its generating process; on the other hand, when the contents shared by Wechat users have very strong time-effectiveness, the most contents can be timely disseminated in Wechat, but the length of the dissemination chain is significantly affected by the theme of the shared contents. This study provides a reference for revealing the complexity of human information behavior.
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