During emergency situations, a quick and concise summary from the deluge of messages improves “situation awareness” and enables informed decisions. However, this is challenging due to the volume, variety, and veracity of information. Grounded in the Situation Awareness Theory, this study presents a streamlined protocol to process millions of social media messages and render them in an easily comprehensible format for various stakeholders to gain deeper insights. Specifically, using a design science approach, we develop a set of artifacts using incremental hierarchical clustering and enhanced text summarization algorithm to produce informative summaries under crisis situations. We implemented our protocol on 2.5 and 3 million tweets collected during the two major hurricanes in 2017 and 2018. The results show that our protocol can derive critical information not captured by Twitter's search tools and mainstream news media and significantly improve on accuracy and efficiency when compared to other contemporary tools.

中文翻译：

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从拼图到肖像：使用设计科学方法增强自然灾害期间的态势感知

在紧急情况下，从大量消息中快速简明地总结可以提高“态势感知”并做出明智的决策。然而，由于信息的数量、多样性和准确性，这具有挑战性。本研究以态势感知理论为基础，提出了一种简化的协议来处理数百万条社交媒体消息，并以一种易于理解的格式呈现它们，供各利益相关者获得更深入的见解。具体来说，使用设计科学方法，我们开发了一组使用增量层次聚类和增强文本摘要算法的工件，以在危机情况下生成信息摘要。我们对 2017 年和 2018 年两次大飓风期间收集的 2.5 和 300 万条推文实施了我们的协议。