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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Network models of financial systemic risk: a review
|
|---|---|
| Published in |
Journal of Computational Social Science, November 2017
|
| DOI | 10.1007/s42001-017-0008-3 |
| Authors |
Fabio Caccioli, Paolo Barucca, Teruyoshi Kobayashi |
X Demographics
The data shown below were collected from the profiles of 10 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 | 2 | 20% |
| Norway | 1 | 10% |
| Italy | 1 | 10% |
| Argentina | 1 | 10% |
| Puerto Rico | 1 | 10% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 60% |
| Scientists | 4 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 153 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 39 | 25% |
| Researcher | 14 | 9% |
| Student > Master | 13 | 8% |
| Other | 8 | 5% |
| Student > Bachelor | 8 | 5% |
| Other | 25 | 16% |
| Unknown | 46 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 47 | 31% |
| Computer Science | 13 | 8% |
| Business, Management and Accounting | 11 | 7% |
| Mathematics | 10 | 7% |
| Social Sciences | 6 | 4% |
| Other | 15 | 10% |
| Unknown | 51 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 21 February 2024.
All research outputs
#4,230,102
of 25,552,205 outputs
Outputs from Journal of Computational Social Science
#44
of 142 outputs
Outputs of similar age
#82,465
of 446,663 outputs
Outputs of similar age from Journal of Computational Social Science
#4
of 11 outputs
Altmetric has tracked 25,552,205 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 142 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.3. This one has gotten more attention than average, scoring higher than 69% 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 446,663 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 81% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.