Title |
Emergence of core–peripheries in networks
|
---|---|
Published in |
Nature Communications, January 2016
|
DOI | 10.1038/ncomms10441 |
Pubmed ID | |
Authors |
T. Verma, F. Russmann, N.A.M. Araújo, J. Nagler, H.J. Herrmann |
Abstract |
A number of important transport networks, such as the airline and trade networks of the world, exhibit a characteristic core-periphery structure, wherein a few nodes are highly interconnected and the rest of the network frays into a tree. Mechanisms underlying the emergence of core-peripheries, however, remain elusive. Here, we demonstrate that a simple pruning process based on removal of underutilized links and redistribution of loads can lead to the emergence of core-peripheries. Links are assumed beneficial if they either carry a sufficiently large load or are essential for global connectivity. This incentivized redistribution process is controlled by a single parameter, which balances connectivity and profit. The obtained networks exhibit a highly resilient and connected core with a frayed periphery. The balanced network shows a higher resilience than the world airline network or the world trade network, revealing a pathway towards robust structural features through pruning. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 19% |
United Kingdom | 4 | 11% |
Canada | 2 | 6% |
Australia | 2 | 6% |
Italy | 2 | 6% |
Belgium | 1 | 3% |
France | 1 | 3% |
Spain | 1 | 3% |
Unknown | 16 | 44% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 19 | 53% |
Scientists | 16 | 44% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 1 | <1% |
United Kingdom | 1 | <1% |
Taiwan | 1 | <1% |
Mexico | 1 | <1% |
United States | 1 | <1% |
Unknown | 119 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 33 | 27% |
Researcher | 18 | 15% |
Student > Master | 13 | 10% |
Professor > Associate Professor | 12 | 10% |
Student > Doctoral Student | 7 | 6% |
Other | 24 | 19% |
Unknown | 17 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 20 | 16% |
Computer Science | 19 | 15% |
Physics and Astronomy | 12 | 10% |
Economics, Econometrics and Finance | 8 | 6% |
Social Sciences | 8 | 6% |
Other | 33 | 27% |
Unknown | 24 | 19% |