| Title |
Sentiment Polarity Detection for Software Development
|
|---|---|
| Published in |
Empirical Software Engineering, September 2017
|
| DOI | 10.1007/s10664-017-9546-9 |
| Authors |
Fabio Calefato, Filippo Lanubile, Federico Maiorano, Nicole Novielli |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 3 | 20% |
| Romania | 1 | 7% |
| Israel | 1 | 7% |
| Norway | 1 | 7% |
| United Kingdom | 1 | 7% |
| India | 1 | 7% |
| Unknown | 7 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 47% |
| Scientists | 7 | 47% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 175 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 175 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 35 | 20% |
| Student > Master | 29 | 17% |
| Student > Bachelor | 12 | 7% |
| Lecturer | 10 | 6% |
| Researcher | 9 | 5% |
| Other | 28 | 16% |
| Unknown | 52 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 85 | 49% |
| Engineering | 8 | 5% |
| Social Sciences | 6 | 3% |
| Business, Management and Accounting | 4 | 2% |
| Decision Sciences | 2 | 1% |
| Other | 11 | 6% |
| Unknown | 59 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 24 January 2023.
All research outputs
#2,216,005
of 23,578,918 outputs
Outputs from Empirical Software Engineering
#40
of 724 outputs
Outputs of similar age
#43,691
of 318,980 outputs
Outputs of similar age from Empirical Software Engineering
#3
of 20 outputs
Altmetric has tracked 23,578,918 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 724 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 94% 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 318,980 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.