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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Building attention and edge message passing neural networks for bioactivity and physical–chemical property prediction
|
|---|---|
| Published in |
Journal of Cheminformatics, January 2020
|
| DOI | 10.1186/s13321-019-0407-y |
| Pubmed ID | |
| Authors |
M. Withnall, E. Lindelöf, O. Engkvist, H. Chen |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 17% |
| Japan | 2 | 17% |
| Argentina | 1 | 8% |
| France | 1 | 8% |
| Comoros | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 75% |
| Scientists | 2 | 17% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 160 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 29 | 18% |
| Researcher | 22 | 14% |
| Student > Master | 19 | 12% |
| Student > Bachelor | 10 | 6% |
| Other | 6 | 4% |
| Other | 18 | 11% |
| Unknown | 56 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 30 | 19% |
| Chemistry | 25 | 16% |
| Engineering | 8 | 5% |
| Agricultural and Biological Sciences | 6 | 4% |
| Biochemistry, Genetics and Molecular Biology | 6 | 4% |
| Other | 22 | 14% |
| Unknown | 63 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 14 December 2022.
All research outputs
#2,197,817
of 24,903,209 outputs
Outputs from Journal of Cheminformatics
#187
of 934 outputs
Outputs of similar age
#51,795
of 469,333 outputs
Outputs of similar age from Journal of Cheminformatics
#9
of 22 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 934 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has done well, scoring higher than 80% 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 469,333 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 88% of its contemporaries.
We're also able to compare this research output to 22 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 63% of its contemporaries.