Mass media as a mirror of the covid-19 pandemic
Yakunin K. Mukhamediev R.I. Zaitseva E. Levashenko V. Yelis M. Symagulov A. Kuchin Y. Muhamedijeva E. Aubakirov M. Gopejenko V.
December 2021MDPI
Computation
2021#9Issue 12
The media plays an important role in disseminating facts and knowledge to the public at critical times, and the COVID-19 pandemic is a good example of such a period. This research is devoted to performing a comparative analysis of the representation of topics connected with the pandemic in the internet media of Kazakhstan and the Russian Federation. The main goal of the research is to propose a method that would make it possible to analyze the correlation between mass media dynamic indicators and the World Health Organization COVID-19 data. In order to solve the task, three approaches related to the representation of mass media dynamics in numerical form—automatically obtained topics, average sentiment, and dynamic indicators—were proposed and applied according to a manually selected list of search queries. The results of the analysis indicate similarities and differences in the ways in which the epidemiological situation is reflected in publications in Russia and in Kazakhstan. In particular, the publication activity in both countries correlates with the absolute indicators, such as the daily number of new infections, and the daily number of deaths. However, mass media tend to ignore the positive rate of confirmed cases and the virus reproduction rate. If we consider strictness of quarantine measures, mass media in Russia show a rather high correlation, while in Kazakhstan, the correlation is much lower. Analysis of search queries revealed that in Kazakhstan the problem of fake news and disinformation is more acute during periods of deterioration of the epidemiological situation, when the level of crime and poverty increase. The novelty of this work is the proposal and implementation of a method that allows the performing of a comparative analysis of objective COVID-19 statistics and several mass media indicators. In addition, it is the first time that such a comparative analysis, between different countries, has been performed on a corpus in a language other than English.
BigARTM , COVID-19 , Latent Dirichlet analysis , Mass media analysis , Topic modeling
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Institute of Information and Computational Technologies MES RK, Pushkin Street, 125, Almaty, 050010, Kazakhstan
Institute of Automation and Information Technologies, Satbayev University, Satpayev Street, 22A, Almaty, 050013, Kazakhstan
School of Engineering Management, Almaty Management University, Rozybakiev Street, 227, Almaty, 050060, Kazakhstan
Faculty of Management Science and Informatics, University of Zilina, Univerzitná 8215/1, Žilina, 010 26, Slovakia
Department of Information Technology, Maharishi International University, 1000 N 4th Street, Fairfield, 52557, IA, United States
International Radio Astronomy Centre, Ventspils University of Applied Sciences, Inzhenieru Street, 101, Ventspils, LV-3601, Latvia
Department of Natural Science and Computer Technologies, ISMA University, Lomonosov Street, 1, Riga, LV-1011, Latvia
Institute of Information and Computational Technologies MES RK
Institute of Automation and Information Technologies
School of Engineering Management
Faculty of Management Science and Informatics
Department of Information Technology
International Radio Astronomy Centre
Department of Natural Science and Computer Technologies
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