Semantic Analysis of Reviews About Organizations Using Machine Learning Methods

21

Abstract

Semantic analysis of organizational reviews is a key tool for assessing customer satisfaction levels. Business entities should regularly conduct analysis and emotional sentiment investigation to delve deeper into the data and gain a more comprehensive understanding of their operations, including through the use of machine learning methods. Presently, deep learning-based methods are garnering increased attention due to their high efficiency. In this study, we will focus on sentiment analysis tasks. To perform sentiment analysis, we will employ machine learning methods, including various approaches to text vectorization, deep learning models, and natural language processing (NLP) algorithms.

General Information

Keywords: natural language processing, classification task, gradient boosting, recurrent neural networks, convolutional neural networks, BERT, GPT

Journal rubric: Data Analysis

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2024140101

Received: 26.02.2024

Accepted:

For citation: Platonov E.N., Martynova I.R. Semantic Analysis of Reviews About Organizations Using Machine Learning Methods. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2024. Vol. 14, no. 1, pp. 7–26. DOI: 10.17759/mda.2024140101. (In Russ., аbstr. in Engl.)

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Information About the Authors

Evgeniy N. Platonov, PhD in Physics and Matematics, Assistant Professor, Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0000-0001-8502-1350, e-mail: en.platonov@gmail.com

Irina Martynova, Student of the Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0009-0007-3140-2490, e-mail: irina.mart.r@gmail.com

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