The data shown below were collected from the profiles of 41 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
How Can Recommender Systems Benefit from Large Language Models: A Survey
|
|---|---|
| Published in |
ACM Transactions on Information Systems, July 2024
|
| DOI | 10.1145/3678004 |
| Authors |
Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Hao Zhang, Yong Liu, Chuhan Wu, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, Weinan Zhang |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Thailand | 1 | 2% |
| Unknown | 40 | 98% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 32 | 78% |
| Scientists | 7 | 17% |
| Science communicators (journalists, bloggers, editors) | 2 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 105 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 15% |
| Student > Ph. D. Student | 10 | 10% |
| Unspecified | 6 | 6% |
| Researcher | 5 | 5% |
| Other | 4 | 4% |
| Other | 9 | 9% |
| Unknown | 55 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 42 | 40% |
| Unspecified | 6 | 6% |
| Physics and Astronomy | 1 | <1% |
| Engineering | 1 | <1% |
| Unknown | 55 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 24 July 2024.
All research outputs
#2,112,009
of 26,583,927 outputs
Outputs from ACM Transactions on Information Systems
#7
of 627 outputs
Outputs of similar age
#25,059
of 295,248 outputs
Outputs of similar age from ACM Transactions on Information Systems
#1
of 11 outputs
Altmetric has tracked 26,583,927 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 627 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 98% 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 295,248 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 91% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.