The Impact of Indirect Connections: The Case of Food Security Problem

Natalia Meshcheryakova

doi:10.1007/978-3-030-05414-4_7

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June 2, 2026

HSE Study Reveals Imbalance in the Generative AI Market

Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.

June 2, 2026

Discovering Science through Russian Language: HSE Prep Year Students Present at International Conference in Kazan

On May 23, 2026, the V International Scientific and Practical Conference ‘Discovering the World of Science’ took place in Kazan at the Preparatory Faculty for International Students of Kazan Federal University. Four students of the HSE International Preparatory Year took part in the event: two delivered their presentations in person, while two participated online. Their work was supervised by Acting Director of the International Prep Year Irina Isaeva and lecturer Ekaterina Kozhemyakova.

May 25, 2026

HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors

Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.

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Publications

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The Impact of Indirect Connections: The Case of Food Security Problem

Ch. 7. P. 80–90.

Natalia Meshcheryakova

We propose a family of new measures for edge importance estimation. We focus on weighted directed networks where weights indicate the intensity of connections between nodes. We reward edges that increase node-tonode influence compared to direct connections between them. This approach allows to reveal hidden channels of the influence in networks. We apply the proposed model to food export/import networks in order to elucidate the most important trading relations. We compare the results with edge-betweenness centrality and investigate the interdependence between edge importance and centrality measures of corresponding source and sink nodes. The results are provided in dynamic.

Keywords: edge importance food security network indirect influence

Publication based on the results of:

A study of models of decision-making and analysis of complex structured data (2019)

In book

Studies in Computational Intelligence

* 2. Vol. 813: Complex Networks and Their Applications VII. , Springer, 2019.

New Centrality Measures in Networks: How to Take into Account the Parameters of the Nodes and Group Influence of Nodes to Nodes

Aleskerov F. T., Shvydun S., Meshcheryakova N., CRC Press, 2022.

Over the last number of years there has been a growing interest in the analysis of complex networks which describe a wide range of real-world systems in nature and society. Identification of the central elements in such networks is one of the key research areas. Solutions to this problem are important for making strategic decisions ...

Added: November 12, 2021