In this paper, the author provides a representation of Italian public hospital facilitators （HFs） （clinics, regional or local community hospitals, and medical centers） by means of different types of networks. Movi...In this paper, the author provides a representation of Italian public hospital facilitators （HFs） （clinics, regional or local community hospitals, and medical centers） by means of different types of networks. Moving from the balance scorecards of HFs, the author has analyzed the representation of those data through the use of the minimum spanning tree （MST） and the planar maximally-filtered graph （PMFG）. This paper firstly examined the amount of information provided by the two networks and then run a sensitivity analysis of the networks by varying the elements of the balance scorecards to be considered. In this way, the author obtained a quite unusual representation of the overall economic situation of Italian HFs. Moreover, the author observed the emergence of patterns which in the author＇s opinion might help policy makers to realize a more efficient allocation of financial resources among the existing HFs.展开更多
Most previous studies have mainly focused on the analyses of one entire network(graph) or the giant connected components of networks. In this paper, we investigate the disconnected components(non-giant connected compo...Most previous studies have mainly focused on the analyses of one entire network(graph) or the giant connected components of networks. In this paper, we investigate the disconnected components(non-giant connected component) of some real social networks, and report some interesting discoveries about structural properties of disconnected components. We study three diverse, real networks and compute the significance profile of each component. We discover some similarities in the local structure between the giant connected component and disconnected components in diverse social networks. Then we discuss how to detect network attacks based on the local structure properties of networks. Furthermore, we propose an empirical generative model called i Friends to generate networks that follow our observed patterns.展开更多
文摘In this paper, the author provides a representation of Italian public hospital facilitators （HFs） （clinics, regional or local community hospitals, and medical centers） by means of different types of networks. Moving from the balance scorecards of HFs, the author has analyzed the representation of those data through the use of the minimum spanning tree （MST） and the planar maximally-filtered graph （PMFG）. This paper firstly examined the amount of information provided by the two networks and then run a sensitivity analysis of the networks by varying the elements of the balance scorecards to be considered. In this way, the author obtained a quite unusual representation of the overall economic situation of Italian HFs. Moreover, the author observed the emergence of patterns which in the author＇s opinion might help policy makers to realize a more efficient allocation of financial resources among the existing HFs.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61572060, 61190125, 61472024)CERNET Innovation Project 2015 (Grant No. NGII20151004)
文摘Most previous studies have mainly focused on the analyses of one entire network(graph) or the giant connected components of networks. In this paper, we investigate the disconnected components(non-giant connected component) of some real social networks, and report some interesting discoveries about structural properties of disconnected components. We study three diverse, real networks and compute the significance profile of each component. We discover some similarities in the local structure between the giant connected component and disconnected components in diverse social networks. Then we discuss how to detect network attacks based on the local structure properties of networks. Furthermore, we propose an empirical generative model called i Friends to generate networks that follow our observed patterns.
