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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Are Happy Developers More Productive?
|
|---|---|
| Chapter number | 7 |
| Book title |
Product-Focused Software Process Improvement
|
| Published in |
Lecture notes in computer science, January 2013
|
| DOI | 10.1007/978-3-642-39259-7_7 |
| Book ISBNs |
978-3-64-239258-0, 978-3-64-239259-7
|
| Authors |
Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson |
X Demographics
The data shown below were collected from the profiles of 28 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 | 7 | 25% |
| United Kingdom | 5 | 18% |
| Brazil | 3 | 11% |
| Germany | 3 | 11% |
| Switzerland | 1 | 4% |
| Canada | 1 | 4% |
| France | 1 | 4% |
| Spain | 1 | 4% |
| Finland | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 5 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 25 | 89% |
| Scientists | 2 | 7% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 32 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 7 | 21% |
| Student > Ph. D. Student | 5 | 15% |
| Student > Bachelor | 4 | 12% |
| Professor | 4 | 12% |
| Student > Doctoral Student | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 7 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 41% |
| Psychology | 4 | 12% |
| Engineering | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 11 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 01 March 2021.
All research outputs
#1,572,871
of 25,315,460 outputs
Outputs from Lecture notes in computer science
#229
of 8,153 outputs
Outputs of similar age
#13,949
of 293,658 outputs
Outputs of similar age from Lecture notes in computer science
#9
of 317 outputs
Altmetric has tracked 25,315,460 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,153 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 97% 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 293,658 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 317 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 97% of its contemporaries.