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Definitional Interpreters for Higher-Order Programming Languages

Overview of attention for article published in Higher-Order & Symbolic Computation, December 1998
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Mentioned by

wikipedia
3 Wikipedia pages

Citations

dimensions_citation
146 Dimensions

Readers on

mendeley
61 Mendeley
citeulike
1 CiteULike
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Title
Definitional Interpreters for Higher-Order Programming Languages
Published in
Higher-Order & Symbolic Computation, December 1998
DOI 10.1023/a:1010027404223
Authors

John C. Reynolds

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Switzerland 1 2%
United Kingdom 1 2%
Taiwan 1 2%
Russia 1 2%
United States 1 2%
Unknown 55 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 21%
Other 11 18%
Student > Bachelor 8 13%
Researcher 8 13%
Student > Master 7 11%
Other 9 15%
Unknown 5 8%
Readers by discipline Count As %
Computer Science 46 75%
Engineering 4 7%
Mathematics 2 3%
Physics and Astronomy 1 2%
Chemistry 1 2%
Other 1 2%
Unknown 6 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 April 2017.
All research outputs
#8,535,684
of 25,374,917 outputs
Outputs from Higher-Order & Symbolic Computation
#16
of 58 outputs
Outputs of similar age
#24,474
of 109,579 outputs
Outputs of similar age from Higher-Order & Symbolic Computation
#4
of 6 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 58 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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 109,579 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
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 2 of them.