6533b834fe1ef96bd129e1f3

RESEARCH PRODUCT

Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

Giacomo FiumaraAnnamaria FicaraAnnamaria FicaraAntonio LiottaPasquale De Meo

subject

Theoretical computer scienceSettore INF/01 - InformaticaComputational complexity theorySocial networkComputer sciencebusiness.industryNode (networking)Complex networksComplex networkSocial network analysisK-pathBetweenness centralityCentrality measuresCorrelation coefficientsCentralitybusinessSocial network analysisClustering coefficient

description

The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the possibility of using them as useful and more economic replacements of the classical centrality measures.

yearjournalcountryeditionlanguage
2021-09-10
https://doi.org/10.1007/978-981-16-1781-2_78