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THE ANALYSIS TECHNIQUE OF SOCIAL MEDIA FOR DISASTER MANAGEMENT

机译:社交媒体灾害管理分析技术

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Social media has transformed mass media based information traffic, and it has become a key resource for finding value in enterprises and public institutions. Particularly, with regard to disaster management, the necessity for public participation in policy development through the use of social media is emphasized. National Disaster Management Research Institute developed the Social Big Board, which is a system that monitors social Big Data in real time for the purpose of implementing social media disaster management. This real time monitoring system provides various information and insights based on the tweets, such as disaster issues, tweet frequency by region, original tweets, etc. The purpose of using this system is to take advantage of the potential benefits of social media in relation to disaster management. In this paper, Korean language text mining based Social Big Board will be briefly introduced, and disaster issue detection model, which is the key algorithms, will be described. The detection model of potential issues of these key algorithms is intensively defined and the performance of the models are compared and evaluated.
机译:社交媒体已经改变了基于大众媒体的信息流量,它已经成为在企业和公共机构中寻找价值的重要资源。特别是在灾害管理方面,强调了公众通过使用社交媒体参与政策制定的必要性。美国国家灾难管理研究院开发了“社会大委员会”,这是一个实时监控社会大数据的系统,目的是实施社会媒体灾难管理。该实时监控系统基于推文提供各种信息和见解,例如灾难问题,按地区发布的推文频率,原始推文等。使用该系统的目的是利用社交媒体相对于灾害管理。在本文中,将简要介绍基于韩文文本挖掘的Social Big Board,并描述作为关键算法的灾难问题检测模型。集中定义了这些关键算法潜在问题的检测模型,并对模型的性能进行了比较和评估。

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