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Using multiplex networks to capture the multidimensional nature of social structure

Overview of attention for article published in Primates, September 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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1 blog
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52 X users

Citations

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42 Dimensions

Readers on

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185 Mendeley
Title
Using multiplex networks to capture the multidimensional nature of social structure
Published in
Primates, September 2018
DOI 10.1007/s10329-018-0686-3
Pubmed ID
Authors

Sandra E. Smith-Aguilar, Filippo Aureli, Laura Busia, Colleen Schaffner, Gabriel Ramos-Fernández

Abstract

Network analysis has increasingly expanded our understanding of social structure in primates and other animal species. However, most studies use networks representing only one interaction type, when social relationships (and the emerging social structure) are the result of many types of interactions and their interplay through time. The recent development of tools facilitating the integrated analysis of multiple interaction types using multiplex networks has opened the possibility of extending the insight provided by social network analysis. We use a multiplex representation of interactions among the members of a group of wild Geoffroy's spider monkeys (Ateles geoffroyi), to study their social structure. We constructed a six-layered multiplex network based on three indices of overt social interactions (aggression, embraces, grooming) and three distance-based indices (contact, proximity, and association). With tools provided by the MuxViz software, we assessed the relevance of including all six indices in our analysis, the role of individuals in the network (through node versatility), and the presence of modules and non-random triadic structures or motifs. The multiplex provided information which was not equivalent to any individual layer or to the simple aggregation of layers. Network patterns based on associations did not correspond with those observed for overt-interactions or for the multiplex structure. Males were the most versatile individuals, while multiplex modularity and motifs highlighted the relevance of different interaction types for the overall connectivity of the network. We conclude that the multiplex approach improves on previous methods by retaining valuable information from each interaction type and how it is patterned among individuals.

X Demographics

X Demographics

The data shown below were collected from the profiles of 52 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 185 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 185 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 49 26%
Researcher 21 11%
Student > Master 17 9%
Student > Bachelor 15 8%
Student > Doctoral Student 9 5%
Other 27 15%
Unknown 47 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 75 41%
Social Sciences 9 5%
Environmental Science 9 5%
Psychology 7 4%
Engineering 5 3%
Other 25 14%
Unknown 55 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 28 November 2023.
All research outputs
#1,105,429
of 25,507,011 outputs
Outputs from Primates
#83
of 1,072 outputs
Outputs of similar age
#23,390
of 348,809 outputs
Outputs of similar age from Primates
#3
of 12 outputs
Altmetric has tracked 25,507,011 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 1,072 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.8. This one has done particularly well, scoring higher than 92% 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 348,809 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 93% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.