KFU. Card publication. Possibilities of Predicting a Person's Substance Use Behaviour and Mental Health Through Social Media in a COVID-19 Crisis Context

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POSSIBILITIES OF PREDICTING A PERSON'S SUBSTANCE USE BEHAVIOUR AND MENTAL HEALTH THROUGH SOCIAL MEDIA IN A COVID-19 CRISIS CONTEXT

Form of presentation

Articles in international journals and collections

Year of publication

2023

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Authors, employees of KFU

Popov Leonid Mikhaylovich, author

Ustin Pavel Nikolaevich, author

Other authors

Konstantinov Vsevolod Valentinovich, author

Bibliographic description in the original language

Konstantinov V, Ustin P, Popov L. Possibilities of Predicting a Person's Substance Use Behaviour and Mental Health Through Social Media in a COVID-19 Crisis Context. OBM Integrative and Complementary Medicine 2023; 8(4): 049

Annotation

The negative psychological consequences of the COVID-19 pandemic and the forced isolation of a large proportion of people worldwide have demonstrated the need to develop ways and technologies to reduce the effects of sudden threats of this type. The basis of any practical work to minimize the negative psychological consequences of the COVID-19 pandemic associated with substance use is the monitoring and diagnosis of the psychological resources of the individual. The article aims to show the possibilities of predicting the behavior of an individual through the content analysis of posts and reposts of their profile on the social network VKontakte on the example of the propensity to use psychoactive substances and to substantiate the possibilities of optimizing and automating such prediction through the use of category markers. Content analysis was carried out by latent semantic analysis of texts extracted from posts and reposts of VKontakte social network users with subsequent content analysis through selecting markers - category words. As a result, a categorical grid was built, which increases the efficiency of content analysis of posts and reposts of users and is suitable for further automation of such research by machine learning methods.

Keywords

COVID-19; social networks; predictors; qualitative analysis; success; personal profile; substance use

The name of the journal

OBM Integrative and Complementary Medicine

On-line resource for training course

http://dspace.kpfu.ru/xmlui/bitstream/handle/net/177567/obm.icm.2304049_Ustin.pdf?sequence=1&isAllowed=y

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=292452&p_lang=2

Resource files

File name	Size (MB)	Format
obm.icm.2304049_Ustin.pdf	0,31	pdf	show / download

Full metadata record

Field DC	Value	Language
dc.contributor.author	Popov Leonid Mikhaylovich	ru_RU
dc.contributor.author	Ustin Pavel Nikolaevich	ru_RU
dc.contributor.author	Konstantinov Vsevolod Valentinovich	ru_RU
dc.date.accessioned	2023-01-01T00:00:00Z	ru_RU
dc.date.available	2023-01-01T00:00:00Z	ru_RU
dc.date.issued	2023	ru_RU
dc.identifier.citation	Konstantinov V, Ustin P, Popov L. Possibilities of Predicting a Person's Substance Use Behaviour and Mental Health Through Social Media in a COVID-19 Crisis Context. OBM Integrative and Complementary Medicine 2023; 8(4): 049	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=292452&p_lang=2	ru_RU
dc.description.abstract	OBM Integrative and Complementary Medicine	ru_RU
dc.description.abstract	The negative psychological consequences of the COVID-19 pandemic and the forced isolation of a large proportion of people worldwide have demonstrated the need to develop ways and technologies to reduce the effects of sudden threats of this type. The basis of any practical work to minimize the negative psychological consequences of the COVID-19 pandemic associated with substance use is the monitoring and diagnosis of the psychological resources of the individual. The article aims to show the possibilities of predicting the behavior of an individual through the content analysis of posts and reposts of their profile on the social network VKontakte on the example of the propensity to use psychoactive substances and to substantiate the possibilities of optimizing and automating such prediction through the use of category markers. Content analysis was carried out by latent semantic analysis of texts extracted from posts and reposts of VKontakte social network users with subsequent content analysis through selecting markers - category words. As a result, a categorical grid was built, which increases the efficiency of content analysis of posts and reposts of users and is suitable for further automation of such research by machine learning methods.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	Possibilities of Predicting a Person's Substance Use Behaviour and Mental Health Through Social Media in a COVID-19 Crisis Context	ru_RU
dc.type	Articles in international journals and collections	ru_RU