A Comparative Analysis of the Transformation of the Other’s Image: 2018-2022

The article is the final in a series of studies we conducted in the period from 2018 to 2022, and focuses on the transformation of the image of the Other in the period of the Covid-19 pandemic. For this study, we used Internet query statistics, extracting a series of markers, which we divided into t...

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Bibliographic Details
Main Authors: Rastyam T. Aliev, Olesya S. Yakushenkova
Format: Article
Language:English
Published: Limited Liability Company Scientific Industrial Enterprise “Genesis. Frontier. Science” 2022-12-01
Series:Галактика медиа: журнал медиа исследований
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Online Access:https://galacticamedia.com/index.php/gmd/article/view/347
Description
Summary:The article is the final in a series of studies we conducted in the period from 2018 to 2022, and focuses on the transformation of the image of the Other in the period of the Covid-19 pandemic. For this study, we used Internet query statistics, extracting a series of markers, which we divided into three groups: food, clothing(appearance), and sexuality. The data was used to compile a correlation matrix and identify the strongest correlation between the markers. The study showed that the most diverse in the number of different markers is the food aspect. The appearance and sexual aspects are less distinctive during the pandemic but also play an important role in shaping the Other's image. It is also worth mentioning the fact that in the post-Covid time (2022) the difference between various models is blurred and some of them are enlarged by the inclusion of representatives of other ethnic groups. In particular, today we can distinguish several big clusters of the Other’s models holding common structural markers: some models are united according to their “food” aspect (Far Eastern cluster), others according to their appearance and sexual aspects (cluster of the former Soviet Union ethnic groups). However, within these clusters, models also share structural markers, so that they can be combined into subgroups based on one feature or another.
ISSN:2658-7734