Abstract:

Users can easily obtain a massive amount of news stories related to an event. But, often the obtained stories are fragmented and can only reflect certain aspects of the event. Detecting the subevents automatically is important for users to understand the whole development process of the event. Motivated by the co-evolution between the event and the opinions about it, we firstly propose to adopt Micro Index and give a dynamic time window construction method based on the recognition of the peaks of the Micro Index Curve. Secondly, we propose a two-stage subevent detection method based on local clustering and classification. And finally, we introduce the news stories about “Luo Yixiao Event” and “Shandong Illegal Vaccines Event”, which are two recent hot events, and use them to evaluate the proposed methods. It is found that the proposed methods are successful.