| Title |
Linguistic neighbourhoods: explaining cultural borders on Wikipedia through multilingual co-editing activity
|
|---|---|
| Published in |
EPJ Data Science, March 2016
|
| DOI | 10.1140/epjds/s13688-016-0070-8 |
| Authors |
Anna Samoilenko, Fariba Karimi, Daniel Edler, Jérôme Kunegis, Markus Strohmaier |
X Demographics
The data shown below were collected from the profiles of 48 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 | 8 | 17% |
| United Kingdom | 4 | 8% |
| Germany | 3 | 6% |
| Italy | 3 | 6% |
| Spain | 2 | 4% |
| Netherlands | 1 | 2% |
| Finland | 1 | 2% |
| Indonesia | 1 | 2% |
| Turkey | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 22 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 26 | 54% |
| Members of the public | 21 | 44% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Netherlands | 1 | 2% |
| Sri Lanka | 1 | 2% |
| Unknown | 51 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 22% |
| Researcher | 7 | 13% |
| Student > Doctoral Student | 5 | 9% |
| Professor > Associate Professor | 4 | 7% |
| Student > Master | 4 | 7% |
| Other | 8 | 15% |
| Unknown | 14 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 22% |
| Social Sciences | 11 | 20% |
| Linguistics | 4 | 7% |
| Business, Management and Accounting | 2 | 4% |
| Arts and Humanities | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 16 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 31. 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 March 2017.
All research outputs
#1,249,989
of 25,307,332 outputs
Outputs from EPJ Data Science
#101
of 436 outputs
Outputs of similar age
#20,705
of 306,492 outputs
Outputs of similar age from EPJ Data Science
#5
of 12 outputs
Altmetric has tracked 25,307,332 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 436 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 done well, scoring higher than 77% 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 306,492 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 93% of its contemporaries.
We're also able to compare this research output to 12 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 66% of its contemporaries.