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

Introduction. 1. Centrality Indices in the Network Analysis. 1.1. Classical Centrality Measures. 1.2. Short and Long-Range Interaction Centrality (LRIC) Indices. 1.3. Power of Nodes Based on Their Interdependence. 1.4. Impact of Indirect Connections in Network Structures. 1.5. Conclusion. 2. Applications. 2.1. Key Borrower Detection in the Global Financial Network. 2.2. Network Analysis of the International Migration. 2.3. Network Analysis of the Global Trade. 2.4. Influence of Countries in the Global Food Network. 2.5. Influence of Countries in the Global Arms Transfers Network. 2.6. Power Distribution in the Networks of Terrorist Groups. 2.7. Network of International Economic Journals. 2.8. Conclusion.

Biography

Professor Fuad Aleskerov graduated from the Mathematical Department of Moscow State University in 1974. He is the Head of the International Center of Decision Choice and Analysis, Head of the Department of Mathematics for Economics, National Research University Higher School of Economics (HSE University); he also holds the Mark Aizerman Chair on Choice Theory and Decision Analysis, Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences. Aleskerov is on the editorial board for 16 journals, has published ten books and more than 150 articles in peer-reviewed journals, and has presented invited papers at more than 160 international conferences. He is a member of several international scientific societies including Academia Europaea.

Sergey Shvydun earned his PhD degree (cum laude) in Applied Mathematics from the National Research University Higher School of Economics (HSE University) in 2020. He is a senior research fellow at HSE's International Center of Decision Choice and Analysis and an associate professor at the Department of Mathematics in the HSE Faculty of Economic Sciences. He is also a senior research fellow at the Laboratory on Choice Theory and Decision Analysis of the Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences. His research interests are in data analysis, social choice theory and social networks analysis.

Natalia Meshcheryakova is a PhD student in Computer Science at the National Research University Higher School of Economics (HSE University). She received a Master Degree of Computer Science from the HSE University in 2018. She is a research fellow at HSE's International Center of Decision Choice and Analysis and a lecturer at the Department of Mathematics in the HSE Faculty of Economic Sciences. She is also a research fellow at the Laboratory on Choice Theory and Decision Analysis of the Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences. Her research interests include social networks, machine learning and data analysis.