Crowdsourcing-based timeline description of urban emergency events using social media

Crowdsourcing is a newly emerging service platform and business model in the Internet. Analysis and description about urban emergency events, e.g., fires, storms and traffic jams are of great importance to protect the security of humans. Recently, social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic. In this paper, in order to describe the timeline of real-time urban emergency events, the new web mining task timeline description (TD) is proposed. Firstly, the related information of an urban emergency event is extracted from Weibo messages. Secondly, the valid message including the semantic or spatial information is detected in this step. Thirdly, detected valid messages are used to build the TD. Case studies on real datasets show the proposed model has good performance and high effectiveness in the analysis and description of urban emergency events.

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