Relation Between News Topics and Variations in Pharmaceutical Indices During COVID-19 Using a Generalized Dirichlet-Multinomial Regression (g-DMR) Model
نویسندگان
چکیده
Owing to the unprecedented COVID-19 pandemic, pharmaceutical industry has attracted considerable attention, spurred by widespread expectation of vaccine development. In this study, we collect relevant topics from news articles related and explore their links with two South Korean indices, Drug Medicine index Korea Composite Stock Price Index (KOSPI) Securities Dealers Automated Quotations (KOSDAQ) Pharmaceutical index. We use generalized Dirichlet-multinomial regression (g-DMR) reveal dynamic topic distributions over metadata values. The results our analysis, obtained using g-DMR, that a greater focus on specific significant relationship fluctuations in indices. also provide practical theoretical implications based analysis. Copyright © 2021 KSII
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ژورنال
عنوان ژورنال: Ksii Transactions on Internet and Information Systems
سال: 2021
ISSN: ['1976-7277', '2288-1468']
DOI: https://doi.org/10.3837/tiis.2021.05.003