Analyzing patterns of user content generation in online social networks

Various online social networks (OSNs) have been developed rapidly on the Internet. Researchers have analyzed different properties of such OSNs, mainly focusing on the formation and evolution of the networks as well as the information propagation over the networks. In knowledge-sharing OSNs, such as blogs and question answering systems, issues on how users participate in the network and how users "generate/contribute" knowledge are vital to the sustained and healthy growth of the networks. However, related discussions have not been reported in the research literature. In this work, we empirically study workloads from three popular knowledge-sharing OSNs, including a blog system, a social bookmark sharing network, and a question answering social network to examine these properties. Our analysis consistently shows that (1) users' posting behavior in these networks exhibits strong daily and weekly patterns, but the user active time in these OSNs does not follow exponential ...

• Type: Conference
• Year: 2009
• Where: KDD
• Authors: Lei Guo, Enhua Tan, Songqing Chen, Xiaodong Zhang, Yihong Eric Zhao
• Keywords: Data Mining, Exponential Distributions, KDD 2009, Online Social Networks, User Posting Behavior