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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Explaining and Interpreting LSTMs
|
|---|---|
| Chapter number | 11 |
| Book title |
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
|
| Published in |
arXiv, September 2019
|
| DOI | 10.1007/978-3-030-28954-6_11 |
| Book ISBNs |
978-3-03-028953-9, 978-3-03-028954-6
|
| Authors |
Leila Arras, José Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek, Jose A. Arjona-Medina |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 2 | 25% |
| France | 1 | 13% |
| Unknown | 5 | 63% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Scientists | 3 | 38% |
Mendeley readers
The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 134 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 29 | 22% |
| Researcher | 21 | 16% |
| Student > Master | 20 | 15% |
| Student > Bachelor | 11 | 8% |
| Student > Doctoral Student | 5 | 4% |
| Other | 18 | 13% |
| Unknown | 30 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 52 | 39% |
| Engineering | 24 | 18% |
| Physics and Astronomy | 4 | 3% |
| Earth and Planetary Sciences | 4 | 3% |
| Economics, Econometrics and Finance | 2 | 1% |
| Other | 16 | 12% |
| Unknown | 32 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 16 December 2019.
All research outputs
#7,158,759
of 25,402,528 outputs
Outputs from arXiv
#119,740
of 916,779 outputs
Outputs of similar age
#118,974
of 351,605 outputs
Outputs of similar age from arXiv
#3,428
of 20,517 outputs
Altmetric has tracked 25,402,528 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 916,779 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 86% 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 351,605 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 20,517 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.