CONTROL CONTRIBUTION IDENTIFIES TOP DRIVER NODES IN COMPLEX NETWORKS

DOI10.1142/S0219525919500140arXiv1906.04663OpenAlexW2998485406WikidataQ126472259 ScholiaQ126472259MaRDI QIDQ6122180

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Publication date: 27 March 2024

Published in: Advances in Complex Systems (Search for Journal in Brave)

Abstract: We propose a new measure to quantify the impact of a node $i$ in controlling a directed network. This measure, called `control contribution' $mathcal{C}_i$, combines the probability for node $i$ to appear in a set of driver nodes and the probability for other nodes to be controlled by $i$. To calculate $mathcal{C}_i$, we propose an optimization method based on random samples of minimum sets of drivers. Using real-world and synthetic networks, we find very broad distributions of $C_i$. Ranking nodes according to their $C_i$ values allows us to identify the top driver nodes that control most of the network. We show that this ranking is superior to rankings based on control capacity or control range. We find that control contribution indeed contains new information that cannot be traced back to degree, control capacity or control range of a node.

Full work available at URL: https://arxiv.org/abs/1906.04663

zbMATH Keywords

complex networkstructural controllabilitydriver nodes

Mathematics Subject Classification ID

Game theory, economics, finance, and other social and behavioral sciences (91-XX)

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