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Analysing expertise through data mining: an example based on treading water

Overview of attention for article published in Journal of Sports Sciences, March 2014
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35 Mendeley
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Article details
Title
Analysing expertise through data mining: an example based on treading water
Published in
Journal of Sports Sciences, March 2014
DOI 10.1080/02640414.2013.876085
Pubmed ID
Authors
Abstract

A classification system of treading water based on a conceptual typology was first established and then verified empirically. The typology was established on two concepts: the nature of the forces created within the water and the type of inter-limb coordination used. Thirty-eight participants were videotaped while treading water. Multivariate statistics were used to understand how the different behavioural types related to expertise. Three distinct groups of coordination patterns were adopted during treading water. A support vector machine procedure was used as a confirmatory procedure. The data mining process provides a methodological framework to analyse expertise in sports activities, and in this context suggests that a taxonomy can be established among the numerous coordination solutions that allow humans to create stabilising forces in the water.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 1 3%
Canada 1 3%
Unknown 33 94%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 9 26%
Student > Ph. D. Student 7 20%
Student > Bachelor 5 14%
Researcher 3 9%
Professor 2 6%
Other 3 9%
Unknown 6 17%
Readers by discipline
Readers by discipline Count As %
Sports and Recreations 18 51%
Psychology 5 14%
Nursing and Health Professions 3 9%
Mathematics 1 3%
Computer Science 1 3%
Other 1 3%
Unknown 6 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 24 June 2014.
All research outputs
#13,409,787
of 22,757,541 outputs
Outputs from Journal of Sports Sciences
#2,770
of 3,777 outputs
Outputs of similar age
#109,828
of 223,408 outputs
Outputs of similar age from Journal of Sports Sciences
#63
of 71 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,777 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one is in the 24th percentile – i.e., 24% 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 223,408 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.