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Public Attitudes on Deadliest Diseases from ۱۵th to ۱۷th Centuries: A Corpus-driven Analysis of Historical Texts

عنوان مقاله: Public Attitudes on Deadliest Diseases from ۱۵th to ۱۷th Centuries: A Corpus-driven Analysis of Historical Texts
شناسه ملی مقاله: JR_RHM-8-2_001
منتشر شده در در سال 1398
مشخصات نویسندگان مقاله:

Amirsaeid Moloodi - Department of foreign languages and linguistics, Shiraz University, Shiraz, Iran
Zahra Montaseri - Ph.D candidate of TEFL, Department of foreign languages and linguistics, Shiraz University, Shiraz, Iran
Mohammad Saber Khaghaninejad - Department of foreign languages and linguistics, Shiraz University, Shiraz, Iran

خلاصه مقاله:
A significant issue in medical health care studies is the representation of illnesses and how they change and affect public attitudes through years. Diachronic corpus-driven linguistics has provided an opportunity for researchers to study these changes in the course of time. Having benefited from a corpus-driven approach and collocations analysis, this study was an attempt to shed light on the representations of six deadly infectious diseases prevailing from ۱۵th to ۱۷th centuries. The chosen corpus for this study was Early English Books Online which includes all the books written within these three centuries. The deadly diseases were selected based on Catalyst Media Network hierarchy of deadliest diseases in human history and their frequencies were first extracted, and then collocations associated with each disease were investigated and reported. Three historical phases of pre-pandemic, pandemic and post-pandemic were considered to categorize the collocations semantically. The analysis of data revealed that public conceptualization of deadly diseases changed from one century to another, as they were initiated, expanded, and treated. The findings might be suggestive for health care researchers, health service training programmers, medical counselors, and policy makers to shape and modify the public attitudes about epidemics consciously.

کلمات کلیدی:
Public attitudes, corpus-driven Analysis, Deadly diseases representations

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1904078/