| Issue |
E3S Web Conf.
Volume 419, 2023
V International Scientific Forum on Computer and Energy Sciences (WFCES 2023)
|
|
|---|---|---|
| Article Number | 02030 | |
| Number of page(s) | 11 | |
| Section | Applied IT Technologies in Energy and Industry | |
| DOI | https://doi.org/10.1051/e3sconf/202341902030 | |
| Published online | 25 August 2023 | |
Model for monitoring the psychological safety of young people based on automated analysis of queries in search engines
1 The Herzen State Pedagogical University of Russia, Psychology Department, Saint Petersburg, Russia
2 ITMO University, Design and Urban Studies Department, Saint Petersburg, Russia
The paper considers the method of parsing and processing information in combination with classical psychological science. The result of the synthesis of the two directions was a predictive model of the mood and psychological state of city residents. The analysis of information about self-destructive practices and the need for psychological assistance based on search engine statistics is one of the most objective analysis tools, since it allows you to evaluate large amounts of information without the influence of social desirability and socio-cultural stereotypes about psychological assistance. The study showed that the analysis of queries in a search engine can serve as an important source of information about psychological security, self-destructive practices and the dynamics of demand for the services of specialists in helping professions. The results of the work can be used to visualize and track the seasonal dynamics of requests for psychological help and monitoring the quality of life of the population. In the course of the work, 30 topics in the field of psychology were analyzed, a database and a predictive model of the psychological state of urban residents based on big data from search engines were developed.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.