The construction of an emergency ontology model plays an important role in emergency management, which is an important basis for emergency public opinion management and decision-making. Integration of network public opinion spread elements into the emergency ontology model is crucial for realizing knowledge sharing in the field of emergency and public opinion responses. In this study, we crawl a large amount of emergency data from different data sources and construct an emergency dataset. Based on this dataset, we analyze the public opinion elements of emergencies and propose an emergency ontology model based on network public opinion spread elements (EOM-NPOSESs). Thereafter, we consider the coronavirus disease (COVID-19) emergency as an example to construct the EOM-NPOSESs. Finally, we design some strategies to realize rule reasoning and present the COVID-19 emergency application based on the constructed EOM-NPOSESs and the geographic information system platform. The results demonstrate that EOM-NPOSESs can not only describe the semantic relationship between emergencies and emergency elements but also perform semantic logical reasoning on different emergencies.

中文翻译：

---

EOM-NPOSESs：基于网络舆情传播元素的应急本体模型

应急本体模型的构建在应急管理中发挥着重要作用，是应急舆情管理和决策的重要依据。将网络舆情传播要素整合到突发事件本体模型中，对于在突发事件和舆情响应领域实现知识共享至关重要。在本研究中，我们从不同的数据源中抓取了大量的应急数据并构建了一个应急数据集。基于该数据集，我们分析了突发事件的舆情要素，提出了基于网络舆情传播要素的突发事件本体模型（EOM-NPOSESs）。此后，我们以冠状病毒病 (COVID-19) 紧急情况为例来构建 EOM-NPOSES。最后，我们设计了一些策略来实现规则推理，并基于构建的 EOM-NPOSES 和地理信息系统平台呈现 COVID-19 应急应用。结果表明，EOM-NPOSESs 不仅可以描述突发事件与突发事件要素之间的语义关系，还可以对不同的突发事件进行语义逻辑推理。