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| Content Provider | PubMed Central |
|---|---|
| Author | Nicosia, V. Criado, R. Romance, M. Russo, G. Latora, V. |
| Copyright Year | 2011 |
| Abstract | Spectral centrality measures allow to identify influential individuals in social groups, to rank Web pages by popularity, and even to determine the impact of scientific researches. The centrality score of a node within a network crucially depends on the entire pattern of connections, so that the usual approach is to compute node centralities once the network structure is assigned. We face here with the inverse problem, that is, we study how to modify the centrality scores of the nodes by acting on the structure of a given network. We show that there exist particular subsets of nodes, called controlling sets, which can assign any prescribed set of centrality values to all the nodes of a graph, by cooperatively tuning the weights of their out-going links. We found that many large networks from the real world have surprisingly small controlling sets, containing even less than 5 – 10% of the nodes. |
| Related Links | http://dx.doi.org/10.1038/srep00218 |
| Starting Page | 218 |
| File Format | |
| ISSN | 20452322 |
| e-ISSN | 20452322 |
| Journal | Scientific Reports |
| Volume Number | 2 |
| Language | English |
| Publisher | Nature Publishing Group |
| Publisher Date | 2012-01-01 |
| Access Restriction | Open |
| Rights Holder | Nature Publishing Group |
| Subject Keyword | Science and technology Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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