Browsing by Author "Atanbekov A."

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    Analysis and development of system for predict psychological portrait of a person
    (2020) Atanbekov A.
    Text content is one of the widespread media types. A question which we are trying to find out in this study is the following: can we identify a psychological portrait or psychological type of a person by given a short text document written by that person? There are different techniques to identify personality types by given text. In this study, the model has been developed to predict the psychological type of the person based on XGBoost. This study is going to explore machine learning algorithms to predict the psychological portrait of a person based on a given text. The psychological portrait will be described by Myers-Briggs Type Indicators (MBTI) which is the most reliable and popular method. This question ‘5 motivated by essays of students at the beginning of their courses to understand their psychological portrait and how it can be met with the profession they choose. The results of this study will help HR specialists and teachers to better understand their students.
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    Prediction of Thinking-Feeling personalities of movie characters
    (2020 International Young Scholars Workshop, 2020) Atanbekov A.; Shirzad H.
    Abstract. This paper is going to explore the difference between the vocabularies used by Thinking and Feeling personalities. To find out this we used the Machine Learning algorithm Naïve Bayes which showed the best accuracy in comparison with others. The concept was motivated by essays of scholars when they submitted the first time at university and to get the full psychological portrait of the student only by given text. To train the model we used a labeled dataset that was collected through a forum with real persons. This dataset contains the type of the person and their posts in social media. To test the model using another dataset which contains information about movie characters and their speech used in the movie. Psycho-type was described by Myers-Briggs Type Indicators (MBTI) which is one of the most popular typologies. To achieve better accuracy of prediction we trained the model separately for Thinking and Feeling predictors. Overall, we achieved better accuracy than previous studies and showed the difference between the vocabularies used by Thinkers and Feelers.