Sociological monitoring of the image of psychiatry and mental illness in social mediaduring the pandemic: results and solutions

Автор: Bogdan Ignat V., Vinogradov Valerii A., Gabov Konstantin I., Iglitsyna Irina S., Kuzmenkov Vladimir A., Chistyakova Darya P.

Журнал: Социальное пространство @socialarea

Рубрика: Социогуманитарные исследования

Статья в выпуске: 3 т.8, 2022 года.

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Stigmatization of psychiatry in the mass consciousness prevents the achievement of effective interaction between the medical sphere and citizens, forms a negative attitude toward all involved in the field of psychiatr. The media often create and broadcast stereotyped and distorted images of medical care, thereby maintaining stigma against psychiatry in the media sphere. In this regard, it is of interest to highlight the patterns of perception. The purpose of the study is to describe the current image of psychiatry and psychiatric diseases in social media. We outline the author’s methodology and methodology of media analysis and the possibility of practical application of the data obtained. The sample consisted of publications in social media in the period from January 2020 to September 2021; we studied only the posts of Moscow residents. Using a neural network, we analyzed an array of 1,396,831 posts. We performed the quantitative analysis using basic Python libraries. As a result, we identified six contexts for discussing psychiatry: “frivolous attitude” to treatment of mental illness including insults; dissemination of information about psychiatry including false information; personal experiences with psychiatry; works of art related to mental health; psychiatry as a public institution; public mental health, in particular its discussion during the pandemic. The research results indicate a high level of stigmatization of mass consciousness. In the future, it is possible, first, to apply the described research methodology in other spheres of the information space in order to identify existing problems and trends, and second, to train the model more and increase its analytical power.

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Covid-19

Короткий адрес: https://sciup.org/147239094

IDR: 147239094   |   DOI: 10.15838/sa.2022.3.35.6

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