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Deciphering Interactions in Moving Animal Groups

Overview of attention for article published in PLoS Computational Biology, September 2012
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

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5 X users
facebook
1 Facebook page
q&a
1 Q&A thread

Readers on

mendeley
269 Mendeley
citeulike
2 CiteULike
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Article details
Title
Deciphering Interactions in Moving Animal Groups
Published in
PLoS Computational Biology, September 2012
DOI 10.1371/journal.pcbi.1002678
Pubmed ID
Authors
Abstract

Collective motion phenomena in large groups of social organisms have long fascinated the observer, especially in cases, such as bird flocks or fish schools, where large-scale highly coordinated actions emerge in the absence of obvious leaders. However, the mechanisms involved in this self-organized behavior are still poorly understood, because the individual-level interactions underlying them remain elusive. Here, we demonstrate the power of a bottom-up methodology to build models for animal group motion from data gathered at the individual scale. Using video tracks of fish shoal in a tank, we show how a careful, incremental analysis at the local scale allows for the determination of the stimulus/response function governing an individual's moving decisions. We find in particular that both positional and orientational effects are present, act upon the fish turning speed, and depend on the swimming speed, yielding a novel schooling model whose parameters are all estimated from data. Our approach also leads to identify a density-dependent effect that results in a behavioral change for the largest groups considered. This suggests that, in confined environment, the behavioral state of fish and their reaction patterns change with group size. We debate the applicability, beyond the particular case studied here, of this novel framework for deciphering interactions in moving animal groups.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 269 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 States 4 1%
United Kingdom 2 <1%
Switzerland 2 <1%
Hungary 1 <1%
Spain 1 <1%
Germany 1 <1%
China 1 <1%
Brazil 1 <1%
Unknown 256 95%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 57 21%
Researcher 41 15%
Student > Master 35 13%
Student > Bachelor 25 9%
Professor > Associate Professor 22 8%
Other 48 18%
Unknown 41 15%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 67 25%
Physics and Astronomy 58 22%
Engineering 28 10%
Computer Science 20 7%
Environmental Science 8 3%
Other 35 13%
Unknown 53 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 10 July 2020.
All research outputs
#7,578,307
of 29,172,250 outputs
Outputs from PLoS Computational Biology
#4,574
of 9,649 outputs
Outputs of similar age
#52,024
of 196,703 outputs
Outputs of similar age from PLoS Computational Biology
#37
of 107 outputs
Altmetric has tracked 29,172,250 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 9,649 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.5. This one has gotten more attention than average, scoring higher than 52% 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 196,703 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 107 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 64% of its contemporaries.