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Common and Unique Network Dynamics in Football Games

Overview of attention for article published in PLOS ONE, December 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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15 X users
facebook
1 Facebook page
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1 Google+ user

Citations

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75 Dimensions

Readers on

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181 Mendeley
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Title
Common and Unique Network Dynamics in Football Games
Published in
PLOS ONE, December 2011
DOI 10.1371/journal.pone.0029638
Pubmed ID
Authors

Yuji Yamamoto, Keiko Yokoyama

Abstract

The sport of football is played between two teams of eleven players each using a spherical ball. Each team strives to score by driving the ball into the opposing goal as the result of skillful interactions among players. Football can be regarded from the network perspective as a competitive relationship between two cooperative networks with a dynamic network topology and dynamic network node. Many complex large-scale networks have been shown to have topological properties in common, based on a small-world network and scale-free network models. However, the human dynamic movement pattern of this network has never been investigated in a real-world setting. Here, we show that the power law in degree distribution emerged in the passing behavior in the 2006 FIFA World Cup Final and an international "A" match in Japan, by describing players as vertices connected by links representing passes. The exponent values γ ~ 3.1 are similar to the typical values that occur in many real-world networks, which are in the range of 2<γ<3, and are larger than that of a gene transcription network, γ ~ 1. Furthermore, we reveal the stochastically switched dynamics of the hub player throughout the game as a unique feature in football games. It suggests that this feature could result not only in securing vulnerability against intentional attack, but also in a power law for self-organization. Our results suggest common and unique network dynamics of two competitive networks, compared with the large-scale networks that have previously been investigated in numerous works. Our findings may lead to improved resilience and survivability not only in biological networks, but also in communication networks.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 181 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 3 2%
United Kingdom 2 1%
Australia 1 <1%
Brazil 1 <1%
Germany 1 <1%
Argentina 1 <1%
United States 1 <1%
Luxembourg 1 <1%
Haiti 1 <1%
Other 0 0%
Unknown 169 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 17%
Student > Master 26 14%
Student > Bachelor 25 14%
Researcher 20 11%
Professor > Associate Professor 11 6%
Other 38 21%
Unknown 30 17%
Readers by discipline Count As %
Sports and Recreations 49 27%
Computer Science 27 15%
Social Sciences 12 7%
Agricultural and Biological Sciences 10 6%
Physics and Astronomy 10 6%
Other 41 23%
Unknown 32 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 03 April 2015.
All research outputs
#2,916,419
of 25,205,864 outputs
Outputs from PLOS ONE
#35,645
of 218,642 outputs
Outputs of similar age
#22,219
of 256,058 outputs
Outputs of similar age from PLOS ONE
#375
of 2,951 outputs
Altmetric has tracked 25,205,864 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 218,642 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one has done well, scoring higher than 83% 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 256,058 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 91% of its contemporaries.
We're also able to compare this research output to 2,951 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.