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DeepGCNs: Making GCNs Go as Deep as CNNs

Overview of attention for article published in IEEE Transactions on Software Engineering, June 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

twitter
50 tweeters

Citations

dimensions_citation
55 Dimensions

Readers on

mendeley
113 Mendeley
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Title
DeepGCNs: Making GCNs Go as Deep as CNNs
Published in
IEEE Transactions on Software Engineering, June 2023
DOI 10.1109/tpami.2021.3074057
Pubmed ID
Authors

Guohao Li, Matthias Müller, Guocheng Qian, Itzel C. Delgadillo, Abdulellah Abualshour, Ali Thabet, Bernard Ghanem

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 50 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 113 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 19%
Student > Master 14 12%
Researcher 12 11%
Student > Doctoral Student 10 9%
Student > Bachelor 10 9%
Other 13 12%
Unknown 32 28%
Readers by discipline Count As %
Computer Science 50 44%
Engineering 14 12%
Unspecified 2 2%
Physics and Astronomy 2 2%
Mathematics 2 2%
Other 9 8%
Unknown 34 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 18 May 2021.
All research outputs
#1,432,057
of 24,503,376 outputs
Outputs from IEEE Transactions on Software Engineering
#81
of 6,109 outputs
Outputs of similar age
#27,278
of 366,916 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#2
of 32 outputs
Altmetric has tracked 24,503,376 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 6,109 research outputs from this source. They receive a mean Attention Score of 4.7. 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 366,916 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 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 96% of its contemporaries.