Title |
Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence
|
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Published in |
PLOS ONE, April 2008
|
DOI | 10.1371/journal.pone.0002051 |
Pubmed ID | |
Authors |
Mark D. Humphries, Kevin Gurney |
Abstract |
Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model--the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 14 | 2% |
United Kingdom | 12 | 1% |
Germany | 9 | <1% |
Netherlands | 5 | <1% |
France | 4 | <1% |
China | 4 | <1% |
Switzerland | 3 | <1% |
Canada | 3 | <1% |
Korea, Republic of | 3 | <1% |
Other | 19 | 2% |
Unknown | 825 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 229 | 25% |
Researcher | 148 | 16% |
Student > Master | 123 | 14% |
Student > Bachelor | 75 | 8% |
Student > Doctoral Student | 51 | 6% |
Other | 136 | 15% |
Unknown | 139 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 121 | 13% |
Computer Science | 101 | 11% |
Neuroscience | 99 | 11% |
Psychology | 85 | 9% |
Engineering | 79 | 9% |
Other | 227 | 25% |
Unknown | 189 | 21% |