[Objective] This study aims to retrieve the trending events from the micro-blog platform with the help of data mining algorithms. [Methods] First, we collected micro-blog message with geographic coordinates from the most popular platform (the Sina Weibo) using its API service. Then, we used the K-means, KNN and decision trees algorithms to construct the geographical patterns of those collected posts. The number of published posts, re-tweets, and comments, as well as user activity and movement strength were also examined. Third, we compared these geographical patterns with the daily regional micro-blog data to identify breaking news in that area. [Results] We analyzed data collected on April 15 and April 16 of 2015 with the help of the proposed model, and found a trending event of “Beijing Sandstorm”. [Limitations] The sample size was small, which might influence the results. [Conclusions] Geographic coordinates could help us detect trending events on the Sina Weibo, and this new method will also support the government’s crisis management strategy and decision-making process.
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