Crowdsourcing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human. Especially, nowadays, no countries, no communities, and no person are immune to urban emergency events. Detection about urban emergency events, e.g., fires, storms, traffic jams is 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. The content from social media usually includes references to urban emergency events occurring at, or affecting specific locations. In this paper, in order to detect and describe the real time urban emergency event, the 5W (What, Where, When, Who, and Why) model is proposed. Firstly, users of social media are set as the target of crowd sourcing. Secondly, the spatial and temporal information from the social media are extracted to detect the real time event. Thirdly, a GIS based annotation of the detected urban emergency event is shown. The proposed method is evaluated with extensive case studies based on real urban emergency events. The results show the accuracy and efficiency of the proposed method.

中文翻译：

---

使用社交媒体大数据基于众包的城市突发事件描述

众包是对城市空间中各种来源（例如传感器、设备、车辆、建筑物和人类）生成的大数据和异构数据进行获取、集成和分析的过程。尤其是在当今，没有哪个国家、没有社区、没有人能够免受城市突发事件的影响。检测城市紧急事件，例如火灾、风暴、交通拥堵，对于保护人类安全具有重要意义。最近，社交媒体提要迅速成为提供和传播通常是地理信息的新平台。来自社交媒体的内容通常包括对发生在或影响特定地点的城市紧急事件的引用。在本文中，为了检测和描述实时城市紧急事件，5W（What、Where、When、Who、和为什么）模型被提出。首先，将社交媒体的用户设置为众包的目标。其次，从社交媒体中提取时空信息以检测实时事件。第三，显示了检测到的城市紧急事件的基于 GIS 的注释。所提出的方法通过基于真实城市紧急事件的广泛案例研究进行评估。结果表明了所提出方法的准确性和有效性。