Graph Model of Information-Psychological Warfare
This study presents a comprehensive graph-based model of information-psychological mental wars, offering a structured approach to understanding the complex mechanisms of influence in hybrid warfare. Building upon an initial hierarchical framework, the authors enhance and expand the model using gener...
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| Дата: | 2025 |
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| Автори: | , |
| Формат: | Стаття |
| Мова: | Ukrainian |
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Інститут проблем реєстрації інформації НАН України
2025
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| Онлайн доступ: | http://drsp.ipri.kiev.ua/article/view/335791 |
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| Назва журналу: | Data Recording, Storage & Processing |
Репозитарії
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drspiprikievua-article-335791 |
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drspiprikievua-article-3357912025-08-09T14:55:54Z Graph Model of Information-Psychological Warfare Графова модель інформаційно-психологічної війни Качинський, А. Б. Ланде, Д. В. ментальні війни, ієрархічна модель, генеративний штучний інтелект, великі мовні моделі, семантична мережа, кластеризація, модульність mental wars, hierarchical model, generative artificial intelligence, large language models, semantic network, clustering, modularity This study presents a comprehensive graph-based model of information-psychological mental wars, offering a structured approach to understanding the complex mechanisms of influence in hybrid warfare. Building upon an initial hierarchical framework, the authors enhance and expand the model using generative artificial intelligence (AI) and large language models (LLMs), enabling the identification of new concepts, clusters, and interconnections that were previously overlooked. The model is structured around five core levels: goals of mental warfare, forces and means, actors, actors' objectives, and implementation policies. These elements are formalized into a directed graph where nodes represent concepts and edges illustrate functional dependencies, forming a semantic network capable of dynamic evolution. By integrating AI-generated insights with expert analysis, the model transitions from a rigid hierarchy to a flexible network structure, allowing for more nuanced and adaptive representations of mental warfare systems. This transformation enables the discovery of non-linear pathways toward strategic outcomes and facilitates more efficient resource allocation. The methodology includes iterative refinement through virtual expert collaboration, linguistic data processing, and visualization tools such as Gephi. The study applies clustering based on modularity classes and node ranking via algorithms like PageRank to identify key influential concepts within the network. Among the most impactful elements identified are disinformation, media manipulation, religion, culture, identity erosion, and economic influence. These findings provide critical insight into the objectives, strategies, and consequences of modern mental warfare, particularly in the context of Russia’s prolonged war against Ukraine. Ultimately, the extended network model enhances analytical capabilities for assessing hybrid threats and offers a robust framework for predicting and countering psychological and informational influence operations. The methodology presented can be applied across various domains requiring deep structural analysis of complex socio-political phenomena. Tabl.: 1. Fig.: 1. Refs: 13 titles. Наведено опис методології створення теоретико-графової моделі «ментальних війн». Для модернізації базової ієрархічної моделі використано генеративний штучний інтелект. Запропоновано методологію розширення моделі новими поняттями, категоріями та зв’язками між ними, що сформовані за допомогою систем штучного інтелекту, великих мовних моделей. За допомогою кластеризації за класами модульнос-ті та ранжування вузлів мережі моделі «ментальних війн», авторами вдосконалено та розширено базову ієрархічну модель, виявлено нові аспекти та покращено розуміння змісту, мети та наслідків інформаційно-психологічних ментальних війн. Інститут проблем реєстрації інформації НАН України 2025-05-20 Article Article application/pdf http://drsp.ipri.kiev.ua/article/view/335791 10.35681/1560-9189.2025.27.1.335791 Data Recording, Storage & Processing; Vol. 27 No. 1 (2025); 99-109 Регистрация, хранение и обработка данных; Том 27 № 1 (2025); 99-109 Реєстрація, зберігання і обробка даних; Том 27 № 1 (2025); 99-109 1560-9189 uk http://drsp.ipri.kiev.ua/article/view/335791/324966 Авторське право (c) 2025 Реєстрація, зберігання і обробка даних |
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Data Recording, Storage & Processing |
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2025-08-09T14:55:54Z |
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OJS |
| language |
Ukrainian |
| topic |
mental wars hierarchical model generative artificial intelligence large language models semantic network clustering modularity |
| spellingShingle |
mental wars hierarchical model generative artificial intelligence large language models semantic network clustering modularity Качинський, А. Б. Ланде, Д. В. Graph Model of Information-Psychological Warfare |
| topic_facet |
ментальні війни ієрархічна модель генеративний штучний інтелект великі мовні моделі семантична мережа кластеризація модульність mental wars hierarchical model generative artificial intelligence large language models semantic network clustering modularity |
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Article |
| author |
Качинський, А. Б. Ланде, Д. В. |
| author_facet |
Качинський, А. Б. Ланде, Д. В. |
| author_sort |
Качинський, А. Б. |
| title |
Graph Model of Information-Psychological Warfare |
| title_short |
Graph Model of Information-Psychological Warfare |
| title_full |
Graph Model of Information-Psychological Warfare |
| title_fullStr |
Graph Model of Information-Psychological Warfare |
| title_full_unstemmed |
Graph Model of Information-Psychological Warfare |
| title_sort |
graph model of information-psychological warfare |
| title_alt |
Графова модель інформаційно-психологічної війни |
| description |
This study presents a comprehensive graph-based model of information-psychological mental wars, offering a structured approach to understanding the complex mechanisms of influence in hybrid warfare. Building upon an initial hierarchical framework, the authors enhance and expand the model using generative artificial intelligence (AI) and large language models (LLMs), enabling the identification of new concepts, clusters, and interconnections that were previously overlooked. The model is structured around five core levels: goals of mental warfare, forces and means, actors, actors' objectives, and implementation policies. These elements are formalized into a directed graph where nodes represent concepts and edges illustrate functional dependencies, forming a semantic network capable of dynamic evolution. By integrating AI-generated insights with expert analysis, the model transitions from a rigid hierarchy to a flexible network structure, allowing for more nuanced and adaptive representations of mental warfare systems. This transformation enables the discovery of non-linear pathways toward strategic outcomes and facilitates more efficient resource allocation. The methodology includes iterative refinement through virtual expert collaboration, linguistic data processing, and visualization tools such as Gephi. The study applies clustering based on modularity classes and node ranking via algorithms like PageRank to identify key influential concepts within the network. Among the most impactful elements identified are disinformation, media manipulation, religion, culture, identity erosion, and economic influence. These findings provide critical insight into the objectives, strategies, and consequences of modern mental warfare, particularly in the context of Russia’s prolonged war against Ukraine. Ultimately, the extended network model enhances analytical capabilities for assessing hybrid threats and offers a robust framework for predicting and countering psychological and informational influence operations. The methodology presented can be applied across various domains requiring deep structural analysis of complex socio-political phenomena. Tabl.: 1. Fig.: 1. Refs: 13 titles. |
| publisher |
Інститут проблем реєстрації інформації НАН України |
| publishDate |
2025 |
| url |
http://drsp.ipri.kiev.ua/article/view/335791 |
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AT kačinsʹkijab graphmodelofinformationpsychologicalwarfare AT landedv graphmodelofinformationpsychologicalwarfare AT kačinsʹkijab grafovamodelʹínformacíjnopsihologíčnoívíjni AT landedv grafovamodelʹínformacíjnopsihologíčnoívíjni |
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2025-09-17T09:26:44Z |
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2025-09-17T09:26:44Z |
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