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 |
Compressed graph representation for scalable molecular graph generation
|
|---|---|
| Published in |
Journal of Cheminformatics, September 2020
|
| DOI | 10.1186/s13321-020-00463-2 |
| Pubmed ID | |
| Authors |
Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Kyoham Shin, Seokho Kang |
X Demographics
The data shown below were collected from the profiles of 7 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 | 14% |
| United Kingdom | 1 | 14% |
| Australia | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 1 | 14% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 27% |
| Student > Ph. D. Student | 5 | 10% |
| Student > Postgraduate | 2 | 4% |
| Professor > Associate Professor | 2 | 4% |
| Student > Master | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 21 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 25% |
| Computer Science | 5 | 10% |
| Engineering | 2 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Physics and Astronomy | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 24 | 50% |
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 17 October 2020.
All research outputs
#6,862,835
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#568
of 891 outputs
Outputs of similar age
#145,045
of 412,380 outputs
Outputs of similar age from Journal of Cheminformatics
#16
of 19 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 36th percentile – i.e., 36% 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 412,380 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 64% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.