| Title |
The Rise of China in the International Trade Network: A Community Core Detection Approach
|
|---|---|
| Published in |
PLOS ONE, August 2014
|
| DOI | 10.1371/journal.pone.0105496 |
| Pubmed ID | |
| Authors |
Zhen Zhu, Federica Cerina, Alessandro Chessa, Guido Caldarelli, Massimo Riccaboni |
| Abstract |
Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism. |
X Demographics
The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 29% |
| Italy | 2 | 12% |
| United States | 2 | 12% |
| Croatia | 1 | 6% |
| Turkey | 1 | 6% |
| Russia | 1 | 6% |
| Isle of Man | 1 | 6% |
| Unknown | 4 | 24% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 71% |
| Scientists | 4 | 24% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 2% |
| Italy | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 63 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 20% |
| Researcher | 11 | 17% |
| Student > Bachelor | 5 | 8% |
| Student > Master | 4 | 6% |
| Lecturer > Senior Lecturer | 3 | 5% |
| Other | 10 | 15% |
| Unknown | 20 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 10 | 15% |
| Social Sciences | 7 | 11% |
| Physics and Astronomy | 6 | 9% |
| Computer Science | 4 | 6% |
| Business, Management and Accounting | 3 | 5% |
| Other | 13 | 20% |
| Unknown | 23 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 January 2018.
All research outputs
#2,971,140
of 23,891,012 outputs
Outputs from PLOS ONE
#38,349
of 204,034 outputs
Outputs of similar age
#30,550
of 237,902 outputs
Outputs of similar age from PLOS ONE
#819
of 4,874 outputs
Altmetric has tracked 23,891,012 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 204,034 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 237,902 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 4,874 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.