As the social networks (such as Sina Weibo) become more and more popular and significant, spammer′s behavior severely affects the cr edibility and readability on social network platforms. A spammer detection model along with the algorithm is proposed based on duplicate detection of microblog posts to detect spammers on Weibo platform. Based on analyses of real-world data, the model is built by considering user behavior information, user social network information and content information. Experiments on a collection of real Weibo data shows the effectiveness of the proposed model. Parameters′ impaction to the model is also studied. The improvement of incorporating behavior information, content information and network information has been analyzed, hence the model is promising.