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X Demographics
Mendeley readers
Attention Score in Context
| Title |
“Failures” to be celebrated: an analysis of major pivots of software startups
|
|---|---|
| Published in |
Empirical Software Engineering, October 2016
|
| DOI | 10.1007/s10664-016-9458-0 |
| Authors |
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen Duc, Pekka Abrahamsson |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 1 | 13% |
| United States | 1 | 13% |
| Germany | 1 | 13% |
| Sweden | 1 | 13% |
| Italy | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 50% |
| Members of the public | 3 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 249 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Czechia | 1 | <1% |
| Italy | 1 | <1% |
| Unknown | 247 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 56 | 22% |
| Student > Ph. D. Student | 31 | 12% |
| Student > Doctoral Student | 17 | 7% |
| Researcher | 13 | 5% |
| Student > Bachelor | 12 | 5% |
| Other | 42 | 17% |
| Unknown | 78 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 63 | 25% |
| Computer Science | 47 | 19% |
| Engineering | 15 | 6% |
| Economics, Econometrics and Finance | 9 | 4% |
| Social Sciences | 6 | 2% |
| Other | 17 | 7% |
| Unknown | 92 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 October 2021.
All research outputs
#6,188,756
of 23,184,056 outputs
Outputs from Empirical Software Engineering
#182
of 710 outputs
Outputs of similar age
#93,674
of 314,677 outputs
Outputs of similar age from Empirical Software Engineering
#9
of 28 outputs
Altmetric has tracked 23,184,056 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 710 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 73% 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 314,677 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 70% 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 has gotten more attention than average, scoring higher than 71% of its contemporaries.