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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Open Source Dataset and Machine Learning Techniques for Automatic Recognition of Historical Graffiti
|
|---|---|
| Chapter number | 37 |
| Book title |
Neural Information Processing
|
| Published in |
arXiv, December 2018
|
| DOI | 10.1007/978-3-030-04221-9_37 |
| Book ISBNs |
978-3-03-004220-2, 978-3-03-004221-9
|
| Authors |
Nikita Gordienko, Peng Gang, Yuri Gordienko, Wei Zeng, Oleg Alienin, Oleksandr Rokovyi, Sergii Stirenko, Gordienko, Nikita, Gang, Peng, Gordienko, Yuri, Zeng, Wei, Alienin, Oleg, Rokovyi, Oleksandr, Stirenko, Sergii |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 9% |
| Ukraine | 1 | 9% |
| Netherlands | 1 | 9% |
| Unknown | 8 | 73% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 91% |
| Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 3 | 27% |
| Student > Ph. D. Student | 3 | 27% |
| Student > Bachelor | 2 | 18% |
| Student > Master | 1 | 9% |
| Researcher | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 1 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 27% |
| Engineering | 2 | 18% |
| Linguistics | 1 | 9% |
| Environmental Science | 1 | 9% |
| Decision Sciences | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 2 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 12 September 2018.
All research outputs
#1,368,666
of 24,099,692 outputs
Outputs from arXiv
#21,315
of 1,020,419 outputs
Outputs of similar age
#32,322
of 444,206 outputs
Outputs of similar age from arXiv
#578
of 26,062 outputs
Altmetric has tracked 24,099,692 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,020,419 research outputs from this source. They receive a mean Attention Score of 4.0. 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 444,206 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 92% of its contemporaries.
We're also able to compare this research output to 26,062 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 97% of its contemporaries.