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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents
|
|---|---|
| Published in |
Research Metrics and Analytics (RMA), March 2021
|
| DOI | 10.3389/frma.2021.654438 |
| Pubmed ID | |
| Authors |
Jiayuan He, Dat Quoc Nguyen, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin, Karin Verspoor |
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 % |
|---|---|---|
| France | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 27% |
| Researcher | 7 | 21% |
| Other | 2 | 6% |
| Student > Doctoral Student | 2 | 6% |
| Professor > Associate Professor | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 9 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 21% |
| Chemistry | 6 | 18% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 9% |
| Unspecified | 1 | 3% |
| Environmental Science | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 12 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 24 April 2021.
All research outputs
#16,734,944
of 25,387,668 outputs
Outputs from Research Metrics and Analytics (RMA)
#252
of 356 outputs
Outputs of similar age
#268,678
of 453,289 outputs
Outputs of similar age from Research Metrics and Analytics (RMA)
#19
of 23 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 356 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.2. This one is in the 26th percentile – i.e., 26% 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 453,289 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.