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As a media and communication platform, microblog is more and more popular around the world. Users can follow anyone ranges from well-known individuals to real friends, and read their tweets without their permission. Most users follow a large number of celebrities and public media in microblog, however, these celebrities do not necessarily follow all their fans. Such one-way relationship abounds in the user network and is displayed in the forms of users' followees and followers, which make it difficult to identify users' real friends who are contained in the merged list of followees and followers. The aim of this paper is to propose a general algorithm for mining users' real friends in social media and dividing them into different social circles automatically according to the closeness of their relationships. To verify the effectiveness of the proposed algorithm, we build a microblog application which presents the social circles for users identified by the algorithm and enable users to modify the proposed results according to her/his real social circles. We demonstrate that our algorithm is superior to traditional clustering method in terms of F measure and Mean Average Precision.