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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments
|
|---|---|
| Published in |
IEEE Transactions on Software Engineering, June 2023
|
| DOI | 10.1109/tpami.2021.3070543 |
| Pubmed ID | |
| Authors |
Roberto Martín-Martín, Mihir Patel, Hamid Rezatofighi, Abhijeet Shenoi, JunYoung Gwak, Eric Frankel, Amir Sadeghian, Silvio Savarese |
Twitter Demographics
The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 20% |
| Japan | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 22% |
| Student > Ph. D. Student | 6 | 15% |
| Researcher | 4 | 10% |
| Student > Doctoral Student | 3 | 7% |
| Student > Postgraduate | 2 | 5% |
| Other | 3 | 7% |
| Unknown | 14 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 11 | 27% |
| Computer Science | 9 | 22% |
| Unspecified | 2 | 5% |
| Psychology | 1 | 2% |
| Mathematics | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 15 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 27 April 2021.
All research outputs
#3,308,372
of 24,093,053 outputs
Outputs from IEEE Transactions on Software Engineering
#434
of 6,072 outputs
Outputs of similar age
#54,093
of 348,644 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#3
of 32 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,072 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 92% 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 348,644 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 84% of its contemporaries.
We're also able to compare this research output to 32 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 93% of its contemporaries.