Microblog searching module based on community detection
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
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Online social networks (OSNs) have become the most popular services on the Internet, and such systems have become part of users' life all over the world. They visit such systems every day and spend more and more time on them. So understanding users' behavior is important to understand such systems. This paper presents results from our measurement on the large-scale OSN spanned by Weibo, the most prevalent and largest microblog system in China at present. Here we talked about two topics: (I) who use Weibo, and (II) what is the users' behavior. We spend one year to persistently observe Weibo, and using API to collect more than 20 million users' profiles to find out that they are and what is their behavior, which is rarely discussed by other researchers. Our studies reveal the users' behavior in Weibo, and we believe our findings make opportunities for in-depth studies of online social network and improve design of such systems.