Topic
Katz centrality
About: Katz centrality is a research topic. Over the lifetime, 601 publications have been published within this topic receiving 77858 citations.
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DOI•
16 Aug 2013
TL;DR: This work proposes a new measurement for the importance of nodes in networks to avoid some shortcomings of classical measurements and argues the limitation of relying on single measurement.
Abstract: Networks are widely used in a variety of different fields and attract more and more researchers. Centrality analyses, one of the research hotspots, provide answers with measures that define the importance of nodes. However, classical centrality analyses usually have high expensive complexity. Moreover, we propose a new measurement for the importance of nodes in networks to avoid some shortcomings of classical measurements. DC centrality integrates two different measurements-degree measurement and cohesion centrality. We also argue the limitation of relying on single measurement. The experiment results show that DC centrality can get better performance.
3 citations
Posted Content•
TL;DR: It is shown that the solution of a standard clearing model commonly used in contagion analyses for financial systems can be expressed as a specific form of a generalized Katz centrality measure under conditions that correspond to a system-wide shock and that clearing models should be given preference over centrality measures in systemic risk analyses.
Abstract: I show that the solution of a standard clearing model commonly used in contagion analyses for financial systems can be expressed as a specific form of a generalized Katz centrality measure under conditions that correspond to a system-wide shock. This result provides a formal explanation for earlier empirical results which showed that Katz-type centrality measures are closely related to contagiousness. It also allows assessing the assumptions that one is making when using such centrality measures as systemic risk indicators. I conclude that these assumptions should be considered too strong and that, from a theoretical perspective, clearing models should be given preference over centrality measures in systemic risk analyses.
3 citations
28 May 2014
TL;DR: It is observed that PPI and Kretschmer can be used as one of the centrality method to determine the leverage level and popular actor of an environment in Twitter.
Abstract: Nowadays, Twitter has become an effective media to communicate as the increasing number of its user. The interaction or relation formed in Twitter could be represented into a graph and calculated using centrality measurement method. Centrality measurement can be used as parameter to determine the popularity or leverage level of an actor towards other actor. The value of centrality measurement is a weighted graph. To maximalize the result, every relation in a graph will be added value from Probabilistic Partnership Index (PPI) method calculation. Furtherly, the analysis and implementation with degree centrality are executed with Kretschmer method using the value from PPI measurement. From the conducted experimental process value, we observed that PPI and Kretschmer can be used as one of the centrality method to determine the leverage level and popular actor of an environment in Twitter.
3 citations
Posted Content•
23 Dec 2013
TL;DR: This work considers a broad class of walk-based, parameterized node centrality measures for network analysis and shows that the parameter can be “tuned” to interpolate between degree and eigenvector centrality, which appear as limiting cases.
Abstract: We consider a broad class of walk-based, parameterized node centrality measures for network analysis. These measures are expressed in terms of functions of the adjacency matrix and generalize various well-known centrality indices, including Katz and subgraph centrality. We show that the parameter can be "tuned" to interpolate between degree and eigenvector centrality, which appear as limiting cases. Our analysis helps explain certain correlations often observed between the rankings obtained using different centrality measures, and provides some guidance for the tuning of parameters. We also highlight the roles played by the spectral gap of the adjacency matrix and by the number of triangles in the network. Our analysis covers both undirected and directed networks, including weighted ones. A brief discussion of PageRank is also given.
3 citations
11 Jun 2012
TL;DR: A novel method based on network cohesion degree measures used in social network analysis to evaluate terrorism network centrality nodes, which shows that this method of efficiency has some advantage over betweenness centrality method.
Abstract: It is important for us to estimate centrality degree of terrorist networks. In this paper, a novel method was presented by us to evaluate terrorism network centrality nodes. The algorithm is based on network cohesion degree measures used in social network analysis. The advantage of this method is to be considered both degree and position of a node. The experimental results show that this method of efficiency has some advantage over betweenness centrality method.
3 citations