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A multilevel statistical toolkit to study animal social networks: Animal Network Toolkit (ANT) R package

View ORCID ProfileSosa Sebastian, View ORCID ProfilePuga-Gonzalez Ivan, Hu Feng He, View ORCID ProfileZhang Peng, Xiaohua Xie, View ORCID ProfileSueur Cédric
doi: https://doi.org/10.1101/347005
Sosa Sebastian
1Anthropology Department, Sun Yat sen University, Primates and Evolution Anthropology Laboratory, Guangzhou, China
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Puga-Gonzalez Ivan
2Institute for Religion, Philosophy and History, University of Agder, Kristiansand, Norway
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Hu Feng He
3School of data science and computer, Sun Yat sen University, Guangzhou, China
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Zhang Peng
1Anthropology Department, Sun Yat sen University, Primates and Evolution Anthropology Laboratory, Guangzhou, China
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Xiaohua Xie
3School of data science and computer, Sun Yat sen University, Guangzhou, China
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Sueur Cédric
2Institute for Religion, Philosophy and History, University of Agder, Kristiansand, Norway
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Abstract

How animals interact and develop social relationships regarding, individual attributes, sociodemographic and ecological pressures is of great interest. New methodologies, in particular Social Network Analysis, allow us to elucidate these types of questions. However, the different methodologies developed to that end and the speed at which they emerge make their use difficult. Moreover, the lack of communication between the different software developed to provide an answer to the same/different research questions is a source of confusion. The R package Animal Network Toolkit (ANT) was developed with the aim of implementing in one package the many different social network analysis techniques currently used in the study of animal social networks. Hence, ANT is a toolkit for animal research allowing among other things to: 1) measure global, dyadic and nodal networks metrics; 2) perform data randomization: pre-network and network (node and link) permutations; 3) perform statistical permutation tests. The package is partially coded in C++ for an optimal coding speed, and it gives researchers a workflow from raw data to the achievement of statistical analyses, allowing for a multilevel approach: from individual position and role within the network, to the identification of interaction patterns, and the analysis of the overall network properties.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 14, 2018.
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A multilevel statistical toolkit to study animal social networks: Animal Network Toolkit (ANT) R package
Sosa Sebastian, Puga-Gonzalez Ivan, Hu Feng He, Zhang Peng, Xiaohua Xie, Sueur Cédric
bioRxiv 347005; doi: https://doi.org/10.1101/347005
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A multilevel statistical toolkit to study animal social networks: Animal Network Toolkit (ANT) R package
Sosa Sebastian, Puga-Gonzalez Ivan, Hu Feng He, Zhang Peng, Xiaohua Xie, Sueur Cédric
bioRxiv 347005; doi: https://doi.org/10.1101/347005

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