| Title |
Detecting bursty terms in computer science research
|
|---|---|
| Published in |
Scientometrics, November 2019
|
| DOI | 10.1007/s11192-019-03307-5 |
| Authors |
E. Tattershall, G. Nenadic, R. D. Stevens |
X Demographics
The data shown below were collected from the profiles of 39 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 | 5 | 13% |
| Germany | 3 | 8% |
| India | 3 | 8% |
| United Kingdom | 2 | 5% |
| Nigeria | 2 | 5% |
| France | 2 | 5% |
| Peru | 1 | 3% |
| Switzerland | 1 | 3% |
| Netherlands | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 16 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 36 | 92% |
| Scientists | 3 | 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% |
| Researcher | 4 | 11% |
| Student > Ph. D. Student | 4 | 11% |
| Lecturer | 2 | 5% |
| Professor > Associate Professor | 2 | 5% |
| Other | 6 | 16% |
| Unknown | 13 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 24% |
| Business, Management and Accounting | 3 | 8% |
| Social Sciences | 3 | 8% |
| Engineering | 2 | 5% |
| Economics, Econometrics and Finance | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 16 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. 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 27 October 2020.
All research outputs
#1,786,480
of 25,389,520 outputs
Outputs from Scientometrics
#323
of 2,911 outputs
Outputs of similar age
#41,506
of 473,336 outputs
Outputs of similar age from Scientometrics
#10
of 55 outputs
Altmetric has tracked 25,389,520 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,911 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done well, scoring higher than 88% 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 473,336 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 91% of its contemporaries.
We're also able to compare this research output to 55 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.