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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The structural and content aspects of abstracts versus bodies of full text journal articles are different
|
|---|---|
| Published in |
BMC Bioinformatics, September 2010
|
| DOI | 10.1186/1471-2105-11-492 |
| Pubmed ID | |
| Authors |
K Bretonnel Cohen, Helen L Johnson, Karin Verspoor, Christophe Roeder, Lawrence E Hunter |
| Abstract |
An increase in work on the full text of journal articles and the growth of PubMedCentral have the opportunity to create a major paradigm shift in how biomedical text mining is done. However, until now there has been no comprehensive characterization of how the bodies of full text journal articles differ from the abstracts that until now have been the subject of most biomedical text mining research. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 33% |
| Sweden | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 4% |
| Australia | 2 | 1% |
| Italy | 2 | 1% |
| Spain | 2 | 1% |
| United Kingdom | 2 | 1% |
| Germany | 1 | <1% |
| Finland | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Netherlands | 1 | <1% |
| Other | 4 | 3% |
| Unknown | 133 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 37 | 24% |
| Student > Ph. D. Student | 31 | 20% |
| Student > Master | 20 | 13% |
| Other | 8 | 5% |
| Student > Bachelor | 8 | 5% |
| Other | 33 | 21% |
| Unknown | 19 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 56 | 36% |
| Agricultural and Biological Sciences | 20 | 13% |
| Linguistics | 10 | 6% |
| Biochemistry, Genetics and Molecular Biology | 7 | 4% |
| Social Sciences | 6 | 4% |
| Other | 33 | 21% |
| Unknown | 24 | 15% |
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 18 January 2022.
All research outputs
#6,927,682
of 25,067,172 outputs
Outputs from BMC Bioinformatics
#2,465
of 7,643 outputs
Outputs of similar age
#32,703
of 104,397 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 54 outputs
Altmetric has tracked 25,067,172 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,643 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 67% 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 104,397 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 68% of its contemporaries.
We're also able to compare this research output to 54 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 68% of its contemporaries.