Patterns of cascading behavior in WeChat moments

WeChat is the largest acquaintance social networking platform in China, which has about 938 million monthly active user accounts. WeChat Moments, known as Friends Circle, serves social networking functions in which users can view information shared by friends. This paper addresses the problem of analyzing the patterns of cascading behavior in WeChat Moments. We obtain 229021 information cascades from WeChat Moments, in which more than 5 million users are involved during 45 days. We analyze these cascades from four aspects to understand the patterns of cascading behavior in WeChat Moments, including the patterns of diffusion structure, temporal dynamic, spatial dynamic and user behavior. In addition, the correlations between these patterns are examined. Our findings contribute to promoting products, predicting and even regulating public opinion.