| Title |
Foreword to the special section on negative results in software engineering
|
|---|---|
| Published in |
Empirical Software Engineering, January 2017
|
| DOI | 10.1007/s10664-017-9498-0 |
| Authors |
Richard F. Paige, Jordi Cabot, Neil A. Ernst |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 3 | 23% |
| Canada | 2 | 15% |
| Germany | 1 | 8% |
| United States | 1 | 8% |
| United Kingdom | 1 | 8% |
| Luxembourg | 1 | 8% |
| Unknown | 4 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 62% |
| Members of the public | 4 | 31% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 25% |
| Professor | 2 | 25% |
| Student > Master | 1 | 13% |
| Researcher | 1 | 13% |
| Student > Postgraduate | 1 | 13% |
| Other | 0 | 0% |
| Unknown | 1 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 38% |
| Business, Management and Accounting | 1 | 13% |
| Medicine and Dentistry | 1 | 13% |
| Unknown | 3 | 38% |
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 13 November 2017.
All research outputs
#3,540,634
of 22,693,205 outputs
Outputs from Empirical Software Engineering
#82
of 705 outputs
Outputs of similar age
#72,667
of 417,744 outputs
Outputs of similar age from Empirical Software Engineering
#7
of 22 outputs
Altmetric has tracked 22,693,205 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 705 research outputs from this source. They receive a mean Attention Score of 4.8. 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 417,744 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 82% 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 has gotten more attention than average, scoring higher than 72% of its contemporaries.