LAUSR

In parallel with the increase of various mobile technologies, the MSN service has brought us into an era of mobile social big data, where people are creating new social data every second and everywhere. It is of vital importance for businesses, governments, and institutions to understand how peoples' behaviors in the online cyberspace can affect the underlying computer network, or their offline behaviors at large. To study this problem, we collect a dataset from WeChat Moments, called WeChatNet, which involves 25,133,330 WeChat users with 246,369,415 records of link reposting on their pages. We revisit three network applications based on the data analytics over WeChatNet, i.e., the information dissemination in mobile cellular networks, the network traffic prediction in backbone networks, and the mobile population distribution projection. We also discuss the potential research opportunities for developing new applications using the released dataset.