The COVID-19 pandemic, as a global health emergency, has attracted considerable attention from the international community. During the pandemic, effective management of COVID-19 by public health authorities depends on the effective dissemination of health-related information. The Corona Disaster Management Headquarters of the Greater Tehran Municipality, as one of the key institutions, developed guidelines for managing the Corona Disaster during the pandemic. However, an initial review of these guidelines shows that their effectiveness has been limited due to linguistic complexity, lack of adaptation to the needs of different audiences, and lack of consistency in the use of vocabulary. This study uses a corpus-based discourse analysis approach to examine the discourse of the guidelines of the Corona Disaster Management Headquarters in the Tehran City Disaster Prevention and Management Organization. A specialized, monolingual, and dynamic corpus with 452,624 words was extracted from 109 PDF files of guidelines related to the Corona Disaster. Data analysis was performed using Sketch Engine and WordSmith software, and high-frequency keywords such as “virus”, “corona”, “hand”, “material”, “disease” and “distance” were identified. The results show that the discourse in the guidelines had limited impact due to linguistic complexity, lack of classification for different audiences and lack of standardization of vocabulary. This research suggests that the effectiveness of Disaster communication can be improved by simplifying linguistic structures, developing guidelines appropriate for different levels of society, and using digital technologies. This study emphasizes the importance of corpus analysis in identifying language patterns and improving Disaster management, and provides a framework for developing effective guidelines in future Disasters.

Keywords: Discourse analysis, corpus, disaster management, Corona, guidelines, keywords.

     

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