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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing
|
---|---|
Chapter number | 1 |
Book title |
Computer Vision – ECCV 2022
|
Published in |
arXiv, October 2022
|
DOI | 10.1007/978-3-031-20059-5_1 |
Book ISBNs |
978-3-03-120058-8, 978-3-03-120059-5
|
Authors |
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie Hyland, Maria Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay, Boecking, Benedikt, Usuyama, Naoto, Bannur, Shruthi, Castro, Daniel C., Schwaighofer, Anton, Hyland, Stephanie, Wetscherek, Maria, Naumann, Tristan, Nori, Aditya, Alvarez-Valle, Javier, Poon, Hoifung, Oktay, Ozan |
X Demographics
The data shown below were collected from the profiles of 32 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 | 6 | 19% |
United Kingdom | 3 | 9% |
France | 1 | 3% |
Netherlands | 1 | 3% |
Brazil | 1 | 3% |
Belgium | 1 | 3% |
Japan | 1 | 3% |
Unknown | 18 | 56% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 21 | 66% |
Scientists | 9 | 28% |
Practitioners (doctors, other healthcare professionals) | 2 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 101 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 24 | 24% |
Researcher | 11 | 11% |
Student > Master | 10 | 10% |
Professor > Associate Professor | 5 | 5% |
Professor | 2 | 2% |
Other | 5 | 5% |
Unknown | 44 | 44% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 30 | 30% |
Engineering | 10 | 10% |
Mathematics | 2 | 2% |
Medicine and Dentistry | 2 | 2% |
Agricultural and Biological Sciences | 1 | <1% |
Other | 5 | 5% |
Unknown | 51 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 01 February 2023.
All research outputs
#2,142,770
of 25,286,324 outputs
Outputs from arXiv
#35,463
of 1,031,847 outputs
Outputs of similar age
#44,297
of 436,816 outputs
Outputs of similar age from arXiv
#1,328
of 39,520 outputs
Altmetric has tracked 25,286,324 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 1,031,847 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 96% 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 436,816 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 89% of its contemporaries.
We're also able to compare this research output to 39,520 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 96% of its contemporaries.