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The goal of the experiment was to find correlations between the information provided within the social network communities and the users\u2019 personalities. Moreover, in this paper, we made an attempt to enhance the results of the classifier accuracy using the sentiment analysis. The experiments were conducted to test the sentiment analysis models, to analyse the proposed feature based on posts\u2019 sentiment, and test the classifier for the detection of the potentially destructive impacts. The analysis of the correlation of the proposed feature with the communities that have potentially destructive impacts on anxiety is conducted. The analysis of the obtained results is provided. During the experiments, the authors found out that consideration of the posts\u2019 sentiment allows increasing accuracy of the classifier for anxiety destructive impacts on 12.24 %. Additionally, we analysed the relationship between the user sentiments metric and destructiveness. We confirmed that the assessment of the user\u2019s posts\u2019 sentiment can be used to compile his psychological characteristics and determine possibility of destructiveness.<\/jats:p>","DOI":"10.3233\/aic-230154","type":"journal-article","created":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T16:51:48Z","timestamp":1723567908000},"page":"585-598","source":"Crossref","is-referenced-by-count":0,"title":["Considerations on sentiment of social network posts as a feature of destructive impacts"],"prefix":"10.1177","volume":"37","author":[{"given":"Diana","family":"Levshun","sequence":"first","affiliation":[{"name":"SPIIRAS, SPC RAS, St. Petersburg, Russia"}]},{"given":"Dmitry","family":"Levshun","sequence":"additional","affiliation":[{"name":"SPIIRAS, SPC RAS, St. Petersburg, Russia"}]},{"given":"Elena","family":"Doynikova","sequence":"additional","affiliation":[{"name":"SPIIRAS, SPC RAS, St. Petersburg, 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