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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The benefits, risks and bounds of personalizing the alignment of large language models to individuals
|
|---|---|
| Published in |
Nature Machine Intelligence, April 2024
|
| DOI | 10.1038/s42256-024-00820-y |
| Authors |
Hannah Rose Kirk, Bertie Vidgen, Paul Röttger, Scott A. Hale |
X Demographics
The data shown below were collected from the profiles of 71 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 Kingdom | 9 | 13% |
| United States | 9 | 13% |
| Canada | 2 | 3% |
| Germany | 2 | 3% |
| Japan | 2 | 3% |
| Italy | 2 | 3% |
| Nigeria | 1 | 1% |
| Zimbabwe | 1 | 1% |
| Korea, Republic of | 1 | 1% |
| Other | 4 | 6% |
| Unknown | 38 | 54% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 39 | 55% |
| Scientists | 28 | 39% |
| Science communicators (journalists, bloggers, editors) | 3 | 4% |
| Practitioners (doctors, other healthcare professionals) | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 33% |
| Unspecified | 2 | 22% |
| Student > Doctoral Student | 1 | 11% |
| Researcher | 1 | 11% |
| Student > Postgraduate | 1 | 11% |
| Other | 1 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 2 | 22% |
| Engineering | 2 | 22% |
| Computer Science | 2 | 22% |
| Mathematics | 1 | 11% |
| Neuroscience | 1 | 11% |
| Other | 1 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 63. 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 May 2024.
All research outputs
#700,709
of 25,997,855 outputs
Outputs from Nature Machine Intelligence
#211
of 791 outputs
Outputs of similar age
#8,348
of 269,866 outputs
Outputs of similar age from Nature Machine Intelligence
#10
of 33 outputs
Altmetric has tracked 25,997,855 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 791 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 68.1. This one has gotten more attention than average, scoring higher than 73% 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 269,866 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 33 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 69% of its contemporaries.