Application of neural network technology for public opinion analysis

The research is devoted to studying and using neural network technologies, in particular algorithms and methods of natural language processing, to increase the efficiency of studying and analyzing public opinion of Ukraine’s partner countries regarding the war in Ukraine. The research involved analyzing and processing databases consisting of messages about the war in Ukraine on the social network Twitter. The resulting datasets were used to train several neural network models. The best classification results were obtained with the GPT-3.5-turbo model. For a deeper understanding of the results of the public opinion analysis, we created their visualization. The results of the study have shown the high efficiency of the selected solutions. They may be of great practical importance for improving methods of analyzing public opinion and making informed decisions based on a deep understanding of global feedback.

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Publication Details

Journal
System research and information technologies
Published
2024-12-25
DOI
https://doi.org/10.20535/srit.2308-8893.2024.4.08
Primary Topic
Advanced Computational Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Application of neural network technology for public opinion analysis

Yuri Parzhin, Kyrylo Perevoznyk
System research and information technologies
Advanced Computational Techniques and Applications
article

Application of neural network technology for public opinion analysis

Yuri Parzhin, Kyrylo Perevoznyk
article en

Abstract

The research is devoted to studying and using neural network technologies, in particular algorithms and methods of natural language processing, to increase the efficiency of studying and analyzing public opinion of Ukraine’s partner countries regarding the war in Ukraine. The research involved analyzing and processing databases consisting of messages about the war in Ukraine on the social network Twitter. The resulting datasets were used to train several neural network models. The best classification results were obtained with the GPT-3.5-turbo model. For a deeper understanding of the results of the public opinion analysis, we created their visualization. The results of the study have shown the high efficiency of the selected solutions. They may be of great practical importance for improving methods of analyzing public opinion and making informed decisions based on a deep understanding of global feedback.

System research and information technologies(4)
National Technical University "Kharkiv Polytechnic Institute" (UA)
Openalex Percentile: Top 74%
Advanced Computational Techniques and Applications
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