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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Auto-CORPus: A Natural Language Processing Tool for Standardizing and Reusing Biomedical Literature
|
|---|---|
| Published in |
Frontiers in Digital Health, February 2022
|
| DOI | 10.3389/fdgth.2022.788124 |
| Pubmed ID | |
| Authors |
Tim Beck, Tom Shorter, Yan Hu, Zhuoyu Li, Shujian Sun, Casiana M. Popovici, Nicholas A. R. McQuibban, Filip Makraduli, Cheng S. Yeung, Thomas Rowlands, Joram M. Posma |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 30% |
| France | 1 | 10% |
| United States | 1 | 10% |
| Switzerland | 1 | 10% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 80% |
| Practitioners (doctors, other healthcare professionals) | 1 | 10% |
| Scientists | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 19% |
| Student > Bachelor | 2 | 13% |
| Lecturer | 1 | 6% |
| Other | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 6 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 25% |
| Computer Science | 2 | 13% |
| Economics, Econometrics and Finance | 1 | 6% |
| Social Sciences | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 7 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 23 February 2023.
All research outputs
#6,325,776
of 25,378,284 outputs
Outputs from Frontiers in Digital Health
#215
of 821 outputs
Outputs of similar age
#144,895
of 563,463 outputs
Outputs of similar age from Frontiers in Digital Health
#18
of 62 outputs
Altmetric has tracked 25,378,284 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 821 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. 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 563,463 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 74% of its contemporaries.
We're also able to compare this research output to 62 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 72% of its contemporaries.