ggtree : an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data

Overview of attention for article published in Methods in Ecology and Evolution, August 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#2 of 915)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
4 blogs
twitter
463 tweeters
peer_reviews
1 peer review site
facebook
3 Facebook pages
googleplus
3 Google+ users

Readers on

mendeley
210 Mendeley
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Title
ggtree : an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data
Published in
Methods in Ecology and Evolution, August 2016
DOI 10.1111/2041-210x.12628
Authors

Yu, Guangchuang, Smith, David K., Zhu, Huachen, Guan, Yi, Lam, Tommy Tsan‐Yuk, Guangchuang Yu, David K. Smith, Huachen Zhu, Yi Guan, Tommy Tsan-Yuk Lam, Greg McInerny

Twitter Demographics

The data shown below were collected from the profiles of 463 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 210 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
Brazil 4 2%
Canada 3 1%
United Kingdom 3 1%
Germany 2 <1%
China 2 <1%
Indonesia 1 <1%
Mexico 1 <1%
Denmark 1 <1%
Other 7 3%
Unknown 181 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 70 33%
Student > Master 46 22%
Researcher 43 20%
Student > Bachelor 12 6%
Student > Postgraduate 11 5%
Other 28 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 166 79%
Biochemistry, Genetics and Molecular Biology 14 7%
Environmental Science 12 6%
Computer Science 4 2%
Immunology and Microbiology 4 2%
Other 10 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 351. 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 22 March 2017.
All research outputs
#12,352
of 7,422,726 outputs
Outputs from Methods in Ecology and Evolution
#2
of 915 outputs
Outputs of similar age
#1,250
of 225,813 outputs
Outputs of similar age from Methods in Ecology and Evolution
#1
of 41 outputs
Altmetric has tracked 7,422,726 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 915 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.6. This one has done particularly well, scoring higher than 99% 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 225,813 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 99% of its contemporaries.
We're also able to compare this research output to 41 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.