Centrality measures are quantitative metrics used in network analysis to determine the relative importance or influence of nodes within a graph. These measures assess various aspects of connectivity, such as degree, closeness, betweenness, and eigenvector centrality, providing insights into the structure and dynamics of complex networks.
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Centrality measures are quantitative metrics used in network analysis to determine the relative importance or influence of nodes within a graph. These measures assess various aspects of connectivity, such as degree, closeness, betweenness, and eigenvector centrality, providing insights into the structure and dynamics of complex networks.
Effective immunization of individual communities with minimal cost in vaccination has made great discussion surrounding the realm of complex networks. Meanwhile, proper realization of relationship among people in society and applying it... more
Effective immunization of individual communities with minimal cost in vaccination has made great discussion surrounding the realm of complex networks. Meanwhile, proper realization of relationship among people in society and applying it to social networks brings about substantial improvements in immunization. Accordingly, weighted graph in which link weights represent the intensity and intimacy of relationships is an acceptable approach. In this work we employ weighted graphs and a wide variety of weighted centrality measures to distinguish important individuals in contagion of diseases. Furthermore, we propose new centrality measures for weighted networks. Our experimental results show that Radiality-Degree centrality is satisfying for weighted BA networks. Additionally, PageRank-Degree and Radiality-Degree centralities showmoreacceptable performance in targeted immunization of weighted networks.