| Title |
Developing a Preliminary Causal Loop Diagram for Understanding the Wicked Complexity of the COVID-19 Pandemic
|
|---|---|
| Published in |
Systems, June 2020
|
| DOI | 10.3390/systems8020020 |
| Authors |
Oz Sahin, Hengky Salim, Emiliya Suprun, Russell Richards, Stefen MacAskill, Simone Heilgeist, Shannon Rutherford, Rodney A. Stewart, Cara D. Beal |
X Demographics
The data shown below were collected from the profiles of 165 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 | 23 | 14% |
| United States | 14 | 8% |
| Australia | 9 | 5% |
| Germany | 7 | 4% |
| Switzerland | 6 | 4% |
| Canada | 6 | 4% |
| South Africa | 5 | 3% |
| Spain | 4 | 2% |
| Italy | 4 | 2% |
| Other | 32 | 19% |
| Unknown | 55 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 130 | 79% |
| Scientists | 21 | 13% |
| Practitioners (doctors, other healthcare professionals) | 7 | 4% |
| Science communicators (journalists, bloggers, editors) | 7 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 199 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 29 | 15% |
| Researcher | 25 | 13% |
| Student > Ph. D. Student | 20 | 10% |
| Student > Doctoral Student | 15 | 8% |
| Student > Bachelor | 12 | 6% |
| Other | 35 | 18% |
| Unknown | 63 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 21 | 11% |
| Engineering | 17 | 9% |
| Environmental Science | 15 | 8% |
| Medicine and Dentistry | 13 | 7% |
| Business, Management and Accounting | 9 | 5% |
| Other | 45 | 23% |
| Unknown | 79 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 126. 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 31 March 2022.
All research outputs
#336,779
of 25,732,188 outputs
Outputs from Systems
#1
of 470 outputs
Outputs of similar age
#10,809
of 435,088 outputs
Outputs of similar age from Systems
#1
of 6 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 470 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 99% 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 435,088 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them