Generalization of effective conductance centrality for egonetworks
| Autor: | Heman Shakeri, Behnaz Moradi-Jamei, Pietro Poggi-Corradini, Nathan Albin, Caterina Scoglio |
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| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
Statistics and Probability Physics - Physics and Society Computer science Generalization FOS: Physical sciences Network science Physics and Society (physics.soc-ph) Topology 01 natural sciences Measure (mathematics) Simple (abstract algebra) Computer Science - Data Structures and Algorithms 0103 physical sciences Data Structures and Algorithms (cs.DS) 0101 mathematics 010306 general physics Social and Information Networks (cs.SI) Degree (graph theory) Node (networking) 010102 general mathematics Conductance Computer Science - Social and Information Networks Condensed Matter Physics Random walk Physics - Data Analysis Statistics and Probability Centrality Data Analysis Statistics and Probability (physics.data-an) |
| Zdroj: | Physica A: Statistical Mechanics and its Applications. 511:127-138 |
| ISSN: | 0378-4371 |
| DOI: | 10.1016/j.physa.2018.07.039 |
| Popis: | We study the popular centrality measure known as effective conductance or in some circles as information centrality. This is an important notion of centrality for undirected networks, with many applications, e.g., for random walks, electrical resistor networks, epidemic spreading, etc. In this paper, we first reinterpret this measure in terms of modulus (energy) of families of walks on the network. This modulus centrality measure coincides with the effective conductance measure on simple undirected networks, and extends it to much more general situations, e.g.,directed networks as well. Secondly, we study a variation of this modulus approach in the egocentric network paradigm. Egonetworks are networks formed around a focal node (ego) with a specific order of neighborhoods. We propose efficient analytical and approximate methods for computing these measures on both undirected and directed networks. Finally, we describe a simple method inspired by the modulus point-of-view, called shell degree, which proved to be a useful tool for network science. |
| Databáze: | OpenAIRE |
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