| Title |
A practical guide to controlled experiments of software engineering tools with human participants
|
|---|---|
| Published in |
Empirical Software Engineering, September 2013
|
| DOI | 10.1007/s10664-013-9279-3 |
| Authors |
Amy J. Ko, Thomas D. LaToza, Margaret M. Burnett |
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 % |
|---|---|---|
| Brazil | 6 | 35% |
| Netherlands | 3 | 18% |
| United States | 2 | 12% |
| Canada | 1 | 6% |
| Israel | 1 | 6% |
| Austria | 1 | 6% |
| Unknown | 3 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 82% |
| Members of the public | 3 | 18% |
Mendeley readers
The data shown below were compiled from readership statistics for 279 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 1% |
| United Kingdom | 2 | <1% |
| Brazil | 2 | <1% |
| Austria | 2 | <1% |
| Turkey | 1 | <1% |
| Indonesia | 1 | <1% |
| Italy | 1 | <1% |
| Germany | 1 | <1% |
| Norway | 1 | <1% |
| Other | 3 | 1% |
| Unknown | 262 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 81 | 29% |
| Student > Master | 48 | 17% |
| Researcher | 26 | 9% |
| Student > Bachelor | 17 | 6% |
| Professor | 14 | 5% |
| Other | 52 | 19% |
| Unknown | 41 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 186 | 67% |
| Engineering | 18 | 6% |
| Business, Management and Accounting | 5 | 2% |
| Social Sciences | 2 | <1% |
| Psychology | 2 | <1% |
| Other | 8 | 3% |
| Unknown | 58 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 07 June 2018.
All research outputs
#2,498,383
of 25,286,324 outputs
Outputs from Empirical Software Engineering
#46
of 770 outputs
Outputs of similar age
#21,681
of 212,065 outputs
Outputs of similar age from Empirical Software Engineering
#2
of 11 outputs
Altmetric has tracked 25,286,324 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 770 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 94% 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 212,065 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 89% 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 done particularly well, scoring higher than 90% of its contemporaries.