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AI and the Origins of the Functional Programming Language Style

Overview of attention for article published in Minds & Machines, May 2017
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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 (#6 of 145)
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
29 tweeters

Readers on

mendeley
7 Mendeley
citeulike
1 CiteULike
Title
AI and the Origins of the Functional Programming Language Style
Published in
Minds & Machines, May 2017
DOI 10.1007/s11023-017-9432-7
Authors

Mark Priestley

Twitter Demographics

The data shown below were collected from the profiles of 29 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 29%
Unspecified 1 14%
Student > Doctoral Student 1 14%
Other 1 14%
Student > Postgraduate 1 14%
Other 1 14%
Readers by discipline Count As %
Computer Science 3 43%
Philosophy 1 14%
Unspecified 1 14%
Psychology 1 14%
Social Sciences 1 14%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 19 January 2018.
All research outputs
#562,985
of 11,655,748 outputs
Outputs from Minds & Machines
#6
of 145 outputs
Outputs of similar age
#24,705
of 266,743 outputs
Outputs of similar age from Minds & Machines
#1
of 6 outputs
Altmetric has tracked 11,655,748 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 145 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 95% 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 266,743 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 90% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them