Effects of anti-epidemic (quarantine) measures on people during the COVID-19 pandemic: applying social network analysis to identify the key topics
https://doi.org/10.20538/1682-0363-2024-4-120-128
Abstract
The aim of this study was to examine the public reaction to the implementation of quarantine measures through a personality-oriented discourse.
Materials and methods. Text data were collected from a microblogging platform, resulting in a dataset of 86,750 texts related to the topics of “pandemic” and “quarantine measures”. The lexical conceptualization of the pandemic and quarantine measures represented in the texts was analyzed through the lens of a personality-oriented discourse. Text lemmatization was conducted using the “snowball” library. A data feature matrix was then created based on the lemmatized tokens, which included 53 tokens with a frequency of use exceeding 1,300 times. The Social Network Analysis (SNA) method was used to create a keyword co-occurrence network consisting of undirected graphs. This analysis was performed using the free software R version 4.4.1, with the assistance of the Quanteda library, built-in “base” packages, and the gsub function.
Results. The resulting network consisted of 53 key lexemes, which actors used to respond to quarantine measures in the personality-oriented discourse. The central node of the network was “coronavirus”, which was used 79,838 times between March 1 and April 30, 2020. The nearest nodes were “test” (used 4,663 times) and “Russia” (used 5,848 times). This network had high centrality, indicating that despite strict restrictive measures, the focus of the general public was on the pandemic itself and its impact on society rather than on the restrictions imposed.
Conclusion. The implementation of these anti-epidemic measures has created a unique sociolinguistic world view, reflecting the interaction between society and the outside world in a time of uncertainty and health risks, affecting the analysis of information and the behavioral strategies chosen by society.
About the Authors
E. K. Pleshkova
National Research Tomsk State University” (NR TSU);
Siberian State Medical University (SSMU)
Russian Federation
Russian Federation
36, Lenina Av., Tomsk, 634050;
2, Moscow Trakt, Tomsk, 634050
Z. I. Rezanova
National Research Tomsk State University” (NR TSU)
Russian Federation
Russian Federation
36, Lenina Av., Tomsk, 634050
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Review
For citations:
Pleshkova E.K., Rezanova Z.I. Effects of anti-epidemic (quarantine) measures on people during the COVID-19 pandemic: applying social network analysis to identify the key topics. Bulletin of Siberian Medicine. 2024;23(4):120-128. https://doi.org/10.20538/1682-0363-2024-4-120-128
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