Using machine learning methods to determine Myers-Briggs Type Index (Mbti) types of people

A. A. Myngzhassar, А. Б. Кульджабеков, S. Daribayev, А. N. Temirbekov

2021

Full text Open access: Gold Metadata (CSL-JSON)

DOI 10.47533/2020.1606-146x.58

Data confidence 70 medium

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Abstract

The article is based on the problems of machine learning in the field of computer linguistics, in particular, the identification of psychological types of people on the basis of text messages on social networks. The purpose of this article is to study the methods of machine learning Naive bayes and Extreme Gradient Boosting (XGBoost) to create a classifier for the Kazakh language, which determines the type of Myers-Briggs Type Index (MBTI) based on text samples of people’s posts on social networks. The course of research experiments in the use of machine learning methods and the results of the study are presented and the results obtained are compared.