You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Delineating the Transnational Network Agenda-Setting Model of Mainstream Newspapers and Twitter: A Machine-Learning Approach
|
|---|---|
| Published in |
Journalism Studies, August 2020
|
| DOI | 10.1080/1461670x.2020.1812421 |
| Authors |
Yan Su, Jun Hu, Danielle Ka Lai Lee |
X Demographics
The data shown below were collected from the profiles of 12 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 States | 2 | 17% |
| China | 1 | 8% |
| Austria | 1 | 8% |
| Unknown | 8 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 50% |
| Scientists | 4 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 8% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 16% |
| Student > Ph. D. Student | 6 | 16% |
| Student > Doctoral Student | 3 | 8% |
| Unspecified | 2 | 5% |
| Lecturer | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 15 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 14 | 38% |
| Arts and Humanities | 3 | 8% |
| Unspecified | 2 | 5% |
| Computer Science | 2 | 5% |
| Economics, Econometrics and Finance | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 15 | 41% |
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 17 November 2020.
All research outputs
#4,087,689
of 24,413,320 outputs
Outputs from Journalism Studies
#568
of 1,230 outputs
Outputs of similar age
#95,877
of 403,454 outputs
Outputs of similar age from Journalism Studies
#15
of 22 outputs
Altmetric has tracked 24,413,320 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 1,230 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has gotten more attention than average, scoring higher than 53% 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 403,454 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 76% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.