Abstract

Numerical data retrieved from the accounts of users of a popular Russian-language online social network have been used to automate the prediction of the PEN test (temperament test) results. This study aims to automate the assessment of personality traits of online social network users by comparing the test results and the content posted by the user on his or her account, using machine learning methods. Classifiers are constructed with CatBoost and random forest models for predicting the scores of extraversion–introversion and neuroticism. The theoretical significance of this result is the development of an approach to automating the assessment of human personality traits. The practical significance is the development of a program module to create an automated system for assessing the human personality traits through online social networks.

中文翻译：

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自动化在线社交网络用户的气质评估

摘要

从流行的俄语在线社交网络用户帐户中检索的数值数据已被用来自动预测 PEN 测试（气质测试）结果。本研究旨在通过使用机器学习方法比较测试结果和用户在其帐户上发布的内容，自动评估在线社交网络用户的性格特征。分类器是用 CatBoost 和随机森林模型构建的，用于预测外向-内向和神经质的分数。这一结果的理论意义在于开发一种自动评估人类人格特征的方法。实际意义在于开发一个程序模块来创建一个通过在线社交网络评估人类性格特征的自动化系统。