With rapid growing popularity, microblogs have become a great source of consumer opinions. Confronting unique properties and massive volume of posts on microblogs, this paper proposes a summarization framework that provides compact numeric summarization for microblogs opinions. The proposed framework is designed to cope with four major tasks: 1) topics detection, 2) sentiment classification, 3) credibility assessment and 4) score aggregation. The experiment is held on twitter, the largest microblog platform, for proving the efficiency and correctness of the framework. We found the consideration of user credibility and opinion quality is essential for aggregating microblog opinions.