Features and Adaptation of Hybrid Information Technologies in Contemporary Literary Criticism under Complex and Dynamics Conditions: Navigating Turbulence, Uncertainty and Systemic Risks within SHIVA-Philology

Main Article Content

Svitlana Krasniuk

Abstract

The article explores the specifics, features and directions of adapting hybrid information technologies to modern literary studies in conditions of turbulence, uncertainty and systemic risks. The potential of SHIVA-philology is substantiated as an integrative model that combines traditional literary interpretation with artificial intelligence, machine learning, natural language processing, big data analysis, knowledge graphs and generative technologies. The principles of hybridization and adaptive application of intelligent technologies for multi-level analysis of a literary text are determined. The prospects for the formation of intellectual platforms that ensure scalability, clarity and sustainability of modern literary studies are shown.

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Data Availability Statement

All data supporting the findings of this study are presented in the text of the scientific work.

Section

Literary studies

Author Biography

Svitlana Krasniuk, Kyiv National University of Technologies and Design

Senior Lecturer, Department of philology and translation

How to Cite

Krasniuk, S. (2026). Features and Adaptation of Hybrid Information Technologies in Contemporary Literary Criticism under Complex and Dynamics Conditions: Navigating Turbulence, Uncertainty and Systemic Risks within SHIVA-Philology. Scientific Collection «InterConf», 309, 69–76. https://interconf.openpubarchive.com/index.php/proceeding/article/view/94

References

Goncharenko S. (2025). Methodological bases of innovative information systems in the field of computer linguistics. Trends, Issues, and Challenges in Modern Science: Proceedings of the 2nd International Scientific Conference (Cambridge, United Kingdom, 5 September 2025). - Lulu Press, Inc., 2025. - P. 100-103. URL: https://er.knutd.edu.ua/handle/123456789/31071

De Luca, E. W., Fallucchi, F., Ghattas, B., & Spielhaus, R. (2024). The digital transformation processes for supporting digital humanities researchers in text analysis. Journal of Documentation, 80 (2), 378–391. https://doi.org/10.1108/JD-07-2022-0143

Zhang, Z., Song, W., & Liu, P. (2024). Making and interpreting: Digital humanities as embodied action. Humanities and Social Sciences Communications, 11, Article 13. https://doi.org/10.1057/s41599-023-02548-3

Zubiaga, A. (2024). Natural language processing in the era of large language models. Frontiers in Artificial Intelligence, 6, Article 1343587. https://doi.org/10.3389/frai.2023.1343587

Goncharenko S. (2025). Intelligent information technologies for innovative management of advanced philology projects. Innovations and New Directions in Scientific Research: Proceedings of the 2nd International Scientific Conference (Manchester, United Kingdom, 20 September 2025). - Lulu Press, Inc., 2025. - P. 176 -179. URL: https://er.knutd.edu.ua/handle/123456789/31648

Smits, T., & Wevers, M. (2023). A multimodal turn in Digital Humanities: Using contrastive machine learning models to explore, enrich, and analyze digital visual historical collections. Digital Scholarship in the Humanities, 38(3), 1267-1280. https://doi.org/10.1093/llc/fqad008

Belém, C. G., Kelly, M., Steyvers, M., Singh, S., & Smyth, P. (2024). Perceptions of linguistic uncertainty by language models and humans. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (pp. 8467 -8502). Associatio n for Computational Linguistics. https://doi.org/10.18653/v1/2024.emnlp-main.483

Baayen, R. H. (2024). The wompom. Corpus Linguistics and Linguistic Theory, 20(3), 615–648. https://doi.org/10.1515/cllt-2024-0053

Hrashchenko, I. S., Krasniuk, M. T., & Krasniuk, S. O. (2019). Hibrydno- stsenarne zastosuvannia intelektualnykh, oriientovanykh na znannia tekhnolohii, yak vazhlyvyi antykryzovyi instrument lohistychnykh kompanii v Ukraini [Hybrid-scenario application of intellectual, knowledge -oriented technologies as an important anti-crisis tool of logistics companies in Ukraine]. Vcheni zapysky Tavriiskoho Natsionalnoho Universytetu imeni VI Vernadskoho. Seriia: Ekonomika i upravlinnia –Scientific notes of Tavri National University named after VI Vernadskyi. Series: Economics and management, 30(69), 121-129.

Краснюк М.Т. (2014). Гібридизація інтелектуальних методів аналізу бізнесових даних (режим виявлення аномалій) як складовий інструмент корпоративного аудиту. Стан і перспективи розвитку обліково інформаційної системи в Україні: матеріали ІІІ Міжнар. наук. -практ. конф. (м. Тернопіль, 10 -11 жовт. 2014 р.). Тернопіль: ТНЕУ, 2014. С. 211-212.

Ait Amine, M., Hmida, M., & Mansouri, K. (2023). Literature Review on Hybrid Evolutionary Approaches for Feature Selection. Algorithms, 16(3), 167. https://doi.org/10.3390/a16030167