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X Demographics
Mendeley readers
Attention Score in Context
| Title |
KMR: knowledge-oriented medicine representation learning for drug–drug interaction and similarity computation
|
|---|---|
| Published in |
Journal of Cheminformatics, March 2019
|
| DOI | 10.1186/s13321-019-0342-y |
| Pubmed ID | |
| Authors |
Ying Shen, Kaiqi Yuan, Min Yang, Buzhou Tang, Yaliang Li, Nan Du, Kai Lei |
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 % |
|---|---|---|
| Sweden | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 22% |
| Student > Master | 10 | 20% |
| Researcher | 7 | 14% |
| Student > Bachelor | 4 | 8% |
| Student > Doctoral Student | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 12 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 28% |
| Engineering | 4 | 8% |
| Chemistry | 4 | 8% |
| Social Sciences | 2 | 4% |
| Business, Management and Accounting | 2 | 4% |
| Other | 7 | 14% |
| Unknown | 17 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 29 August 2022.
All research outputs
#2,662,179
of 23,202,641 outputs
Outputs from Journal of Cheminformatics
#265
of 858 outputs
Outputs of similar age
#61,152
of 352,002 outputs
Outputs of similar age from Journal of Cheminformatics
#8
of 23 outputs
Altmetric has tracked 23,202,641 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 858 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 68% 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 352,002 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 82% of its contemporaries.
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 has gotten more attention than average, scoring higher than 65% of its contemporaries.