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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Optimising chemical named entity recognition with pre-processing analytics, knowledge-rich features and heuristics
|
|---|---|
| Published in |
Journal of Cheminformatics, January 2015
|
| DOI | 10.1186/1758-2946-7-s1-s6 |
| Pubmed ID | |
| Authors |
Riza Batista-Navarro, Rafal Rak, Sophia Ananiadou |
X Demographics
The data shown below were collected from the profiles of 8 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 | 3 | 38% |
| United Kingdom | 1 | 13% |
| Switzerland | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 88% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 3% |
| Croatia | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 61 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 25% |
| Researcher | 11 | 17% |
| Student > Master | 8 | 12% |
| Student > Bachelor | 7 | 11% |
| Student > Doctoral Student | 5 | 8% |
| Other | 6 | 9% |
| Unknown | 12 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 29 | 45% |
| Engineering | 5 | 8% |
| Chemistry | 3 | 5% |
| Agricultural and Biological Sciences | 3 | 5% |
| Business, Management and Accounting | 2 | 3% |
| Other | 7 | 11% |
| Unknown | 16 | 25% |
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 16 March 2015.
All research outputs
#6,455,251
of 23,577,654 outputs
Outputs from Journal of Cheminformatics
#544
of 872 outputs
Outputs of similar age
#86,709
of 356,031 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 17 outputs
Altmetric has tracked 23,577,654 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 872 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
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 356,031 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 75% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.