You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improving biomedical named entity recognition with syntactic information
|
|---|---|
| Published in |
BMC Bioinformatics, November 2020
|
| DOI | 10.1186/s12859-020-03834-6 |
| Pubmed ID | |
| Authors |
Yuanhe Tian, Wang Shen, Yan Song, Fei Xia, Min He, Kenli Li |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 25% |
| Sweden | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 16% |
| Student > Ph. D. Student | 6 | 9% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 5 | 8% |
| Student > Master | 5 | 8% |
| Other | 10 | 16% |
| Unknown | 23 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 25 | 39% |
| Agricultural and Biological Sciences | 4 | 6% |
| Engineering | 3 | 5% |
| Social Sciences | 2 | 3% |
| Unspecified | 1 | 2% |
| Other | 3 | 5% |
| Unknown | 26 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 04 May 2021.
All research outputs
#3,759,323
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#1,335
of 7,400 outputs
Outputs of similar age
#99,097
of 510,659 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 169 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 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 81% 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 510,659 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 80% of its contemporaries.
We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.