DOI: https://doi.org/10.32515/2664-262X.2025.12(43).2.20-26

Method of Integral Analysis of Relationships between Information Sources based on Temporal-Semantic Metrics

Artem Kalancha, Dmytro Uhryn, Oleksandr Dorenskyi, Vasyl Lytvyn

About the Authors

Artem Kalancha, PhD Student, Department of Computer System Software, Yuriy Fedkovych Chernivtsi National University, Сernivtsi, Ukraine, ORCID: https://orcid.org/0009-0004-1451-7470, e-mail: kalancha.artem@chnu.edu.ua

Dmytro Uhryn, Professor, Doctor of Technical Sciences, Professor of the Department of Computer Science, Yuriy Fedkovych Chernivtsi National University, Chernivtsi, Ukraine, ORCID: https://orcid.org/0000-0003-4858-4511, e-mail: d.ugryn@chnu.edu.ua

Oleksandr Dorenskyi, Associate Professor, PhD in Information Technology (Candidate of Technical Sciences), Associate Professor of Cybersecurity and Software Department, Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine, ORCID: https://orcid.org/0000-0002-7625-9022, e-mail: dorenskyiop@kntu.kr.ua

Vasyl Lytvyn, Doctor of Technical Sciences, Professor of the Department of Information Systems and Networks, Lviv Polytechnic National University, Lviv, Ukraine, ORCID: https://orcid.org/0000-0002- 9676-0180, e-mail: vasyl.v.lytvyn@lpnu.ua

Abstract

This study is devoted to the analysis of the relationships between information sources in the Ukrainian information space, in particular between news and political Telegram channels. The paper identifies the main shortcomings of existing analysis methods, which are mainly focused on the English-language context and do not take into account the dynamic nature of information sources. As an alternative to these methods, a new method of integral analysis is proposed, which combines several independent metrics at the same time - lexical similarity and temporal-semantic influence. The proposed and implemented approach allows us to assess not only the semantic similarity of sources, but also the nature of their interactions over time, forming a multidimensional matrix of relationships. The results obtained demonstrate the effectiveness of the integral approach for identifying hidden structures of information influence, which can be used for the further development of monitoring systems.

Keywords

Artificial Intelligence, NLP, Information Flows, Information Sources, Integrated Analysis, Network Structures, Temporal Semantic Influence

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References

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Citations

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