OVED-Rank: A ranking scheme to evaluate complex network spreaders’ influence through the concept of effective distance and orbital velocity

Abstract

This paper explores the influence of complex network spreaders, which is the most studied problems in network science. However, developing an efficient technique to handle this task remains challenging due to its NP-hard nature. Several traditional approaches to identifying the influence of complex network spreaders usually rely on algorithms for determining network paths that are more complex, such as Dijkstra’s algorithm or Bellman-Ford’s algorithm, which require significant computational resources and do not always take into account the location of nodes in a network. To cope with these issues, this paper proposes a new method called OVED-Rank, which is inspired by the orbital velocity formula for the influence of key spreaders in complex networks. It incorporates an advanced metric effective distance replacing traditional measures like Dijkstra’s distance to streamline computations and decrease processing times. OVED-Rank combines the degree of a node, the k-shell index, the number of triangles that form part of a node, and the length of paths connecting the nodes. Unlike traditional methods, OVED-Rank does not rely on the usual complex shortest-path algorithms. Instead, it uses effective distance, which makes the calculations easier and less complex. In addition, it improves predictability by taking into account the characteristics of neighboring nodes. The robustness and effectiveness of OVED-Rank are thoroughly vetted through rigorous testing on various network, including both synthetic setups and real-world undirected, unweighted networks. The experimental results are compelling, indicating that OVED-Rank not only meets but often exceeds the performance of existing methodologies.