EOM-NPOSESs: Emergency Ontology Model Based on Network Public Opinion Spread Elements

Abstract

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.

Network Public Opinion Risk Prediction and Judgment Based on Deep Learning: A Model of Text Sentiment Analysis

“…Because the public opinion environment of the social networking platform is more open, free, and private than that of real society, and because public publishing and obtaining information in the network is more convenient and faster than exploring, publicizing, or querying information in the real world, more and more people pay attention to daily hot spots or public events through the Internet [1][2][3][4][5]. When people fnd the information they are interested in in the process of browsing the Internet, many people will express their own opinions and opinions on the content of the information, and the information containing the emotional tendencies and subjective attitudes of netizens constitutes a new network public opinion information [6][7][8][9]. By analyzing some network public opinion with a strong emotional attitude, we can fnd that there is not only a lot of positive public opinion information with healthy, positive, and positive energy but also some false, pessimistic, and reactionary negative opinion information.…”

Codca – Covid-19 Ontology for Data Collection and Analysis in E-Health

“…Protégé is used for development and SPARQL is used for querying. called Coronavirus Infectious Diseases Ontology (CIDO) for investigation (Dong et al, 2021). proposed an emergency ontology model called EOM-NPOSESs.…”