| Title |
Negative results for software effort estimation
|
|---|---|
| Published in |
Empirical Software Engineering, November 2016
|
| DOI | 10.1007/s10664-016-9472-2 |
| Authors |
Tim Menzies, Ye Yang, George Mathew, Barry Boehm, Jairus Hihn |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
| Sweden | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 1% |
| Unknown | 95 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 18% |
| Student > Master | 17 | 18% |
| Professor | 9 | 9% |
| Researcher | 7 | 7% |
| Student > Bachelor | 6 | 6% |
| Other | 22 | 23% |
| Unknown | 18 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 56 | 58% |
| Engineering | 10 | 10% |
| Business, Management and Accounting | 3 | 3% |
| Agricultural and Biological Sciences | 1 | 1% |
| Philosophy | 1 | 1% |
| Other | 2 | 2% |
| Unknown | 23 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 20 November 2017.
All research outputs
#7,204,447
of 23,007,053 outputs
Outputs from Empirical Software Engineering
#247
of 707 outputs
Outputs of similar age
#130,884
of 415,855 outputs
Outputs of similar age from Empirical Software Engineering
#16
of 33 outputs
Altmetric has tracked 23,007,053 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 707 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 64% 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 415,855 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 33 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 51% of its contemporaries.