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A roadmap for the computation of persistent homology

Overview of attention for article published in EPJ Data Science, August 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#49 of 377)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

news
1 news outlet
policy
1 policy source
twitter
56 tweeters
patent
1 patent
facebook
5 Facebook pages
wikipedia
3 Wikipedia pages
googleplus
1 Google+ user

Citations

dimensions_citation
318 Dimensions

Readers on

mendeley
408 Mendeley
Title
A roadmap for the computation of persistent homology
Published in
EPJ Data Science, August 2017
DOI 10.1140/epjds/s13688-017-0109-5
Pubmed ID
Authors

Nina Otter, Mason A Porter, Ulrike Tillmann, Peter Grindrod, Heather A Harrington

Twitter Demographics

The data shown below were collected from the profiles of 56 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 408 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
United States 2 <1%
Singapore 1 <1%
Slovenia 1 <1%
Poland 1 <1%
Unknown 401 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 96 24%
Researcher 66 16%
Student > Master 45 11%
Student > Bachelor 28 7%
Professor 21 5%
Other 81 20%
Unknown 71 17%
Readers by discipline Count As %
Mathematics 89 22%
Computer Science 69 17%
Physics and Astronomy 46 11%
Engineering 33 8%
Neuroscience 16 4%
Other 70 17%
Unknown 85 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 53. 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 17 January 2023.
All research outputs
#678,323
of 22,981,247 outputs
Outputs from EPJ Data Science
#49
of 377 outputs
Outputs of similar age
#15,811
of 317,964 outputs
Outputs of similar age from EPJ Data Science
#5
of 11 outputs
Altmetric has tracked 22,981,247 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 377 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.1. This one has done well, scoring higher than 87% 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 317,964 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 95% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.