Title |
Augmenting and structuring user queries to support efficient free-form code search
|
---|---|
Published in |
Empirical Software Engineering, January 2018
|
DOI | 10.1007/s10664-017-9544-y |
Authors |
Raphael Sirres, Tegawendé F. Bissyandé, Dongsun Kim, David Lo, Jacques Klein, Kisub Kim, Yves Le Traon |
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 % |
---|---|---|
Luxembourg | 2 | 40% |
United States | 1 | 20% |
Korea, Republic of | 1 | 20% |
Unknown | 1 | 20% |
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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 67 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 16 | 24% |
Student > Master | 12 | 18% |
Student > Doctoral Student | 5 | 7% |
Lecturer | 4 | 6% |
Other | 3 | 4% |
Other | 9 | 13% |
Unknown | 18 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 39 | 58% |
Engineering | 5 | 7% |
Business, Management and Accounting | 1 | 1% |
Unknown | 22 | 33% |
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 10 May 2019.
All research outputs
#6,869,666
of 23,041,514 outputs
Outputs from Empirical Software Engineering
#215
of 709 outputs
Outputs of similar age
#139,572
of 440,596 outputs
Outputs of similar age from Empirical Software Engineering
#15
of 28 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 709 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 69% 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 440,596 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 28 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.