Social Network Analysis (SNA) is used to study the exchange of resources among individuals, groups, or organizations. The role of individuals or connections in a network is described by a set of centrality metrics which represent one of the most important results of SNA. Degree, closeness, betweenness and clustering coefficient are the most used centrality measures. Their use is, however, severely hampered by their computation cost. This issue can be overcome by an algorithm called Game of Thieves (GoT). Thanks to this new algorithm, we can compute the importance of all elements in a network (i.e. vertices and edges), compared to the total number of vertices. This calculation is done not in a quadratic time, as when we use the classical methods, but in polylogarithmic time. Starting from this we present our results on the correlation existing between GoT and the most widely used centrality measures. From our experiments emerge that a strong correlation exists, which makes GoT eligible as a centrality measure for large scale complex networks.

Ficara A., Fiumara G., De Meo P., Liotta A. (2021). Correlations Among Game of Thieves and Other Centrality Measures in Complex Networks. In G. Fortino, A. Liotta, R. Gravina, A. Longheu (a cura di), Data Science and Internet of Things - Research and Applications at the Intersection of DS and IoT (pp. 43-62). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-67197-6_3].

Correlations Among Game of Thieves and Other Centrality Measures in Complex Networks

Ficara A.
;
Fiumara G.;De Meo P.;
2021-01-01

Abstract

Social Network Analysis (SNA) is used to study the exchange of resources among individuals, groups, or organizations. The role of individuals or connections in a network is described by a set of centrality metrics which represent one of the most important results of SNA. Degree, closeness, betweenness and clustering coefficient are the most used centrality measures. Their use is, however, severely hampered by their computation cost. This issue can be overcome by an algorithm called Game of Thieves (GoT). Thanks to this new algorithm, we can compute the importance of all elements in a network (i.e. vertices and edges), compared to the total number of vertices. This calculation is done not in a quadratic time, as when we use the classical methods, but in polylogarithmic time. Starting from this we present our results on the correlation existing between GoT and the most widely used centrality measures. From our experiments emerge that a strong correlation exists, which makes GoT eligible as a centrality measure for large scale complex networks.
2021
Settore INF/01 - Informatica
Ficara A., Fiumara G., De Meo P., Liotta A. (2021). Correlations Among Game of Thieves and Other Centrality Measures in Complex Networks. In G. Fortino, A. Liotta, R. Gravina, A. Longheu (a cura di), Data Science and Internet of Things - Research and Applications at the Intersection of DS and IoT (pp. 43-62). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-67197-6_3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/552238
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