Перегляд за Автор "Gavrilenko, O."

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    Software architecture for creating a psychological portrait of a person based on social media activity
    (КПІ ім. Ігоря Сікорського, 2025) Mytnyk, D.; Gavrilenko, O.; Bogdanova, N.
    In this paper, we have developed and implemented a software architecture for creating a psychological portrait of a person based on social media activity. A modern person spends a lot of time on social media and leaves a digital footprint there that is highly correlated with their psychological characteristics. Based on social media data, we can understand behavioral patterns, a person's temperament type, etc. The aim of this study is to automate the construction of a psychological portrait of a person based on social media activity. This paper focuses on the use of the personality model approach to formalize a psychological portrait, namely the Big Five and the Myers-Briggs Type Indicator (MBTI). Accordingly, a mathematical formulation of the problem was developed. In accordance with the created formulation, this task was formalized as a multi-label classification problem and a neural network approach was used to solve it. We decided to use a large language models approach as at the time of writing this architecture shows state-of-the-art results on most natural language processing tasks. The Large Language Model Meta AI architecture was chosen as the neural network architecture. The scientific novelty is the use of the multitask finetuning approach for this task. The instruction tuning dataset was built based on the «Essays I» and «MBTI Dataset» datasets. The study proved that using this approach can significantly improve the model's results compared to training on each task separately. A distributed architecture for analyzing social media posts was designed and implemented. Further work includes improving the accuracy of the neural network by collecting more data and introducing feedback mechanisms. The article also presents the intended use of the system and its limitations. The results of this study are important for such areas as human resources, marketing or forensics.
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    The algorithm for predicting the cryptocurrency rate taking into account the influence of posts of a group of famous people in social networks
    (КПІ ім. Ігоря Сікорського, 2023) Bidyuk, P.; Gavrilenko, O.; Myagkyi, M.
    Abstract. This article presents an algorithm for predicting the rate of a selected cryptocurrency, taking into account the posts of a group of famous people in a par ticular social network. The celebrities chosen as experts, i.e., famous personalities whose posts on social networks were studied, are either familiar with the financial industry, particularly the cryptocurrency market, or some cryptocurrency. The data set used was the actual rates of the cryptocurrency in question for the selected period and the statistics of expert posts in the selected social network. The study used methods such as the full probability formula and the Bayesian formula. It was found that posts by famous people on social media differently affected cryptocurrency rates. The “main” expert was identified, and his posts were used to forecast the se lected cryptocurrency’s rate.