| Title |
Mining open datasets for transparency in taxi transport in metropolitan environments
|
|---|---|
| Published in |
EPJ Data Science, December 2015
|
| DOI | 10.1140/epjds/s13688-015-0060-2 |
| Pubmed ID | |
| Authors |
Anastasios Noulas, Vsevolod Salnikov, Renaud Lambiotte, Cecilia Mascolo |
X Demographics
The data shown below were collected from the profiles of 38 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 | 6 | 16% |
| United Kingdom | 4 | 11% |
| Italy | 4 | 11% |
| France | 2 | 5% |
| Canada | 2 | 5% |
| India | 1 | 3% |
| Finland | 1 | 3% |
| Mexico | 1 | 3% |
| Spain | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 15 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 27 | 71% |
| Scientists | 10 | 26% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 1% |
| Indonesia | 1 | 1% |
| Austria | 1 | 1% |
| United States | 1 | 1% |
| Luxembourg | 1 | 1% |
| Poland | 1 | 1% |
| Unknown | 73 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 27% |
| Student > Ph. D. Student | 15 | 19% |
| Student > Bachelor | 6 | 8% |
| Lecturer | 6 | 8% |
| Researcher | 5 | 6% |
| Other | 13 | 16% |
| Unknown | 13 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 22 | 28% |
| Engineering | 13 | 16% |
| Social Sciences | 6 | 8% |
| Earth and Planetary Sciences | 4 | 5% |
| Business, Management and Accounting | 3 | 4% |
| Other | 13 | 16% |
| Unknown | 18 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. 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 11 January 2016.
All research outputs
#1,383,911
of 25,522,520 outputs
Outputs from EPJ Data Science
#119
of 447 outputs
Outputs of similar age
#22,857
of 395,701 outputs
Outputs of similar age from EPJ Data Science
#4
of 9 outputs
Altmetric has tracked 25,522,520 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 447 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.3. 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 395,701 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 94% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.