Social media has already become an important part of daily life. Entering the era of smart phone, people always share their created contents anywhere anytime. Among the created contents, the microblog has become a mapping of human life, which can clearly express natural human emotion and mood. In this paper, we demonstrate how social media content generated by microblog can be used to predict real-world economics trends. Especially, we used the most popular Chinese microblog services Sina Weibo to provide the collective big data for forecasting China economics trends such as China's Shanghai securities (SSE) composite index. A simple model built based on the social mood at which Weibo are created about people emotion can outperform market-based predictors. We further demonstrate how sentiments extracted from Weibo can be further utilized to improve the predicting power of social media.
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