Kateryna Potapova

Work place: Department of System Programming and Specialized Computer Systems, Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine

E-mail: avatarkina-avatarochka@ukr.net


Research Interests: Artificial Intelligence


Kateryna Potapova: Ph.D, associate professor of the Department of System Programming and Specialized Computer Systems Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine.
Research Interests: Control Systems and Information Technology, Computer Systems and Networks Software, Intelligence and Expert Systems, Neural Networks and Image Processing, Artificial Intelligence, Machine Learning. 

Author Articles
Augmenting Sentiment Analysis Prediction in Binary Text Classification through Advanced Natural Language Processing Models and Classifiers

By Zhengbing Hu Ivan Dychka Kateryna Potapova Vasyl Meliukh

DOI: https://doi.org/10.5815/ijitcs.2024.02.02, Pub. Date: 8 Apr. 2024

Sentiment analysis is a critical component in natural language processing applications, particularly for text classification. By employing state-of-the-art techniques such as ensemble methods, transfer learning and deep learning architectures, our methodology significantly enhances the robustness and precision of sentiment predictions. We systematically investigate the impact of various NLP models, including recurrent neural networks and transformer-based architectures, on sentiment classification tasks. Furthermore, we introduce a novel ensemble method that combines the strengths of multiple classifiers to improve the predictive ability of the system. The results demonstrate the potential of integrating state-of-the-art Natural Language Processing (NLP) models with ensemble classifiers to advance sentiment analysis. This lays the foundation for a more advanced comprehension of textual sentiments in diverse applications.

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