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Innovations in News Media: Crisis Classification System

机译:新闻媒体的创新:危机分类系统

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Research in crisis management is a relatively new area of study, originating in the 1980s. Researchers have created several different models that separate organizational crises into discrete stages, such as pre-crisis, crisis and post-crisis. In this article we discuss a natural language based crisis detection system which classifies news articles relating to crises into the appropriate crisis stage. We use news articles from the New York Times as a source of training data, and use this data along with state of the art data mining and machine learning algorithms as the core of the system. In the future, our system may be expanded to identify and evaluate crisis management strategies, suggest crisis management strategies for the current state of a crisis, or provide stakeholders with summaries of crises in news media.
机译:危机管理方面的研究是一个相对较新的研究领域,起源于1980年代。研究人员创建了几种不同的模型,将组织危机分为离散的阶段,例如危机前,危机和危机后。在本文中,我们讨论了一种基于自然语言的危机检测系统,该系统将与危机相关的新闻文章分类为适当的危机阶段。我们将来自《纽约时报》的新闻文章用作培训数据的来源,并将此数据与最新的数据挖掘和机器学习算法一起用作系统的核心。将来,我们的系统可能会扩展为识别和评估危机管理策略,为当前危机状态建议危机管理策略,或向利益相关者提供新闻媒体中的危机摘要。

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