Abstract

The possible role played by individual attributes, sociodemographic characteristics and/or ecological pressures in the interaction between animals and the development of social relationships between them is of great interest in animal ecology and evolutionary biology. Social Network Analysis is an ideal tool to study these types of questions. The Animal Network Toolkit Software (ANTs) R package was specifically developed to provide all the different social network analysis techniques currently used in the study of animal social networks. This global package enables users to (1) compute global, polyadic and nodal network measures; (2) perform data randomisation: data stream and network (node and link) permutations; (3) perform statistical permutation tests for static or temporal network analyses, and (4) visualise networks. ANTs allows researchers to perform multilevel network analyses ranging from individual network measures to interaction patterns and the analysis of the overall network structure, and carry out static or temporal network analyses without switching between different R packages, thus making a substantial contribution to advances in the study of animal behaviour. ANTs outperforms existing R packages for the computation speed of network measures and permutations.

Details

Title
A multilevel statistical toolkit to study animal social networks: the Animal Network Toolkit Software (ANTs) R package
Author
Sosa, Sebastian 1 ; Puga-Gonzalez, Ivan 2 ; Hu Fenghe 3 ; Pansanel Jérôme 4 ; Xie Xiaohua 3 ; Sueur Cédric 5 

 Sun Yat-Sen University, Primate and Evolution Anthropology Laboratory, Anthropology Department, Guangzhou, China (GRID:grid.12981.33) (ISNI:0000 0001 2360 039X); Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France (GRID:grid.11843.3f) (ISNI:0000 0001 2157 9291) 
 University of Agder, Institute for Religion, Philosophy and History, Kristiansand, Norway (GRID:grid.23048.3d) (ISNI:0000 0004 0417 6230) 
 Sun Yat-Sen University, School of Data and Computer Science, Guangzhou, China (GRID:grid.12981.33) (ISNI:0000 0001 2360 039X) 
 Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France (GRID:grid.11843.3f) (ISNI:0000 0001 2157 9291) 
 Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France (GRID:grid.11843.3f) (ISNI:0000 0001 2157 9291); Institut Universitaire de France, Paris, France (GRID:grid.440891.0) (ISNI:0000 0001 1931 4817) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2427390918
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.