Title |
Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks
|
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Published in |
PLOS ONE, January 2013
|
DOI | 10.1371/journal.pone.0053095 |
Pubmed ID | |
Authors |
Mahendra Piraveenan, Mikhail Prokopenko, Liaquat Hossain |
Abstract |
A number of centrality measures are available to determine the relative importance of a node in a complex network, and betweenness is prominent among them. However, the existing centrality measures are not adequate in network percolation scenarios (such as during infection transmission in a social network of individuals, spreading of computer viruses on computer networks, or transmission of disease over a network of towns) because they do not account for the changing percolation states of individual nodes. We propose a new measure, percolation centrality, that quantifies relative impact of nodes based on their topological connectivity, as well as their percolation states. The measure can be extended to include random walk based definitions, and its computational complexity is shown to be of the same order as that of betweenness centrality. We demonstrate the usage of percolation centrality by applying it to a canonical network as well as simulated and real world scale-free and random networks. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Venezuela, Bolivarian Republic of | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 2% |
United Kingdom | 3 | 2% |
Hungary | 1 | <1% |
China | 1 | <1% |
Canada | 1 | <1% |
Unknown | 185 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 49 | 25% |
Researcher | 31 | 16% |
Student > Master | 28 | 14% |
Student > Doctoral Student | 11 | 6% |
Student > Bachelor | 11 | 6% |
Other | 31 | 16% |
Unknown | 33 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 28 | 14% |
Agricultural and Biological Sciences | 27 | 14% |
Engineering | 24 | 12% |
Mathematics | 13 | 7% |
Physics and Astronomy | 10 | 5% |
Other | 49 | 25% |
Unknown | 43 | 22% |