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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Will this localization tool be effective for this bug? Mitigating the impact of unreliability of information retrieval based bug localization tools
|
|---|---|
| Published in |
Empirical Software Engineering, December 2016
|
| DOI | 10.1007/s10664-016-9484-y |
| Authors |
Tien-Duy B. Le, Ferdian Thung, David Lo |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| United States | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 1 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 2% |
| Unknown | 49 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 20% |
| Student > Master | 8 | 16% |
| Researcher | 5 | 10% |
| Student > Bachelor | 3 | 6% |
| Student > Doctoral Student | 2 | 4% |
| Other | 8 | 16% |
| Unknown | 14 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 32 | 64% |
| Engineering | 3 | 6% |
| Agricultural and Biological Sciences | 1 | 2% |
| Unknown | 14 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 09 October 2017.
All research outputs
#13,335,574
of 23,003,906 outputs
Outputs from Empirical Software Engineering
#375
of 706 outputs
Outputs of similar age
#206,390
of 420,472 outputs
Outputs of similar age from Empirical Software Engineering
#24
of 33 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 706 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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 420,472 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 50% 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 is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.