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As hundreds of millions of users access online social communities at daily or even real-time basis, large amounts of user data are continuously generated. The fast-growing user-generated content poses great challenges on online social network system design for efficient content management and delivery. For instance, in content-centric online social network, all contents are organized in a temporal order which makes it very time consuming for users to browse all these contents to locate what they really like. By conducting a comprehensive study of online user activities, including content, social, and time characteristics, this paper try to accurately characterize user interest and user context, with the end goal of more efficient content management and real-time content delivery in online social network systems. The detail analysis of user activities is conducted on the real data collected from a popular online social community among Chinese universities with over 63,000 users to demonstrate the advantage and effectiveness of extracting user interest and context characteristics and applying them in designing more efficient content management systems.