A trace-driven analysis on the user behaviors in social e-commerce network

Abstract

E-commerce has become one of the common commercial activities in people's daily lives. The major advantage of e-commerce over conventional commercial activities is the information transparency while people can freely share their opinions and comments. Such information has profound influence on user behaviors in e-commerce activities. Meanwhile, social network service (SNS) has also become the most popular way to get and share information on the Internet. Therefore, it is quite natural to put e-commerce and SNS together. Recently, there emerge many online social e-commerce network (SECON) services, which not only allow users to conduct e-commerce transactions but also enable users to share information as in the other SNS like Twitter. Although conventional SNS has been widely investigated, little is known about SECON. To address this problem, we conduct a trace-driven analysis on a successful SECON called Jumei, with millions of users. Our analysis is based on shared information and all activities they created, all these data are crawled from the website of Jumei. We shed light on the user activity characteristics in SECON. By analyzing the crawled data, we discover that the social ties have an important influence on commercial activities. However, to our surprise, there are many differences between SECON and SNS: (a) the network topology structure is greatly different from SNS, (b) strong ties play a more crucial role than in SNS, same to viral marketing intuition, and (c) the behavior of adoption activity is influenced weakly by peers in the social network, for example, nearly 60% users influenced by only one information propagated from social links before they decided to buy it. Furthermore, we find that it takes a long time to adopt what their followees have bought.