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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The textual characteristics of traditional and Open Access scientific journals are similar
|
|---|---|
| Published in |
BMC Bioinformatics, June 2009
|
| DOI | 10.1186/1471-2105-10-183 |
| Pubmed ID | |
| Authors |
Karin Verspoor, K Bretonnel Cohen, Lawrence Hunter |
| Abstract |
Recent years have seen an increased amount of natural language processing (NLP) work on full text biomedical journal publications. Much of this work is done with Open Access journal articles. Such work assumes that Open Access articles are representative of biomedical publications in general and that methods developed for analysis of Open Access full text publications will generalize to the biomedical literature as a whole. If this assumption is wrong, the cost to the community will be large, including not just wasted resources, but also flawed science. This paper examines that assumption. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 10% |
| United Kingdom | 2 | 4% |
| Australia | 1 | 2% |
| Germany | 1 | 2% |
| Spain | 1 | 2% |
| Indonesia | 1 | 2% |
| Unknown | 39 | 78% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 32% |
| Student > Ph. D. Student | 7 | 14% |
| Other | 6 | 12% |
| Professor | 4 | 8% |
| Lecturer | 3 | 6% |
| Other | 10 | 20% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 34% |
| Agricultural and Biological Sciences | 7 | 14% |
| Linguistics | 5 | 10% |
| Arts and Humanities | 3 | 6% |
| Psychology | 3 | 6% |
| Other | 8 | 16% |
| Unknown | 7 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 16 November 2016.
All research outputs
#2,838,734
of 22,707,247 outputs
Outputs from BMC Bioinformatics
#982
of 7,255 outputs
Outputs of similar age
#11,043
of 112,212 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 39 outputs
Altmetric has tracked 22,707,247 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,255 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 86% 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 112,212 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 90% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.