Recently, there are an increasing number of researches focusing on discovering real-world events from microblog. However, most of existing work ignore the importance of emotion information for event detection. We argue that people’s emotional reactions immediately reflect the occurring of real-world events and should be important for event detection. In this study, we focus on the problem of community-related event detection by community emotions. To address the problem, we propose a novel framework which include the following three key components: microblog emotion classification, community emotion aggregation and community emotion burst detection. We evaluate our approach on real microblog data sets. Experimental results demonstrate the effectiveness of the proposed framework.