Project

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

Goal: How animals interact and develop social relationships in face of sociodemographic and ecological pressures is of great interest. New methodologies, in particular Social Network Analysis (SNA), 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 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- and post-network (node and link permutations); 3) perform statistical permutation tests as correlation test, t-test, General Linear Model, General Linear Mixed Model, deletion simulation, Matrix TauKr correlations , MRQAP. The package is partially coded in C++ using the R package Rcpp for an optimal coding speed. The package gives researchers a workflow from the raw data to the achievement of statistical analyses, allowing for a multilevel approach: from the individual’s position and role within the network, to the identification of interactional patterns, and the study of the overall network properties. Furthermore, ANT also provides a guideline on the SNA techniques used: 1) from the appropriate randomization technique according to the data collected; 2) to the choice, the meaning, the limitations and advantages of the network metrics to apply, 3) and the type of statistical tests to run. The ANT project is multi-collaborative, aiming to provide access to advanced social network analysis techniques and to create new ones that meet researchers’ needs in future versions.

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Cédric Sueur
added a research item
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.
Sebastian Sosa Orozco
added an update
I present in this video 1) what is ANT, 2) the goal, 3) where did the idea come from, 4) how it is structured and 5) an example of ANT analytical protocol.
ANT official website: http://s-sosa.com/ant
My personal website: http://s-sosa.com/
 
Sebastian Sosa Orozco
added an update
ANT holds 48 network metrics and more are coming!
1. Degree
2. Outdegree
3. Indegree
4. Strength
5. Outstrengh
6. Instrengh
7. Eigenvector weighted
8. Eigenvector binary
9. Weighted Affinity
10. Binary Affinity
11. Reach
12. Disparity
13. R-index
14. Weighted Laplacian centrality
15. Binary Laplacian centrality
16. Binary density
17. Weighted undirected betweenness
18. Weighted directed betweenness
19. Weighted undirected normalize betweenness
20. Weighted directed normalize betweenness
21. Binary undirected betweenness
22. Binary directed betweenness
23. Weighted directed diameter
24. Weighted undirected diameter
25. Weighted directed normalize diameter
26. Weighted undirected normalize diameter
27. Weighted directed Stronger weights diameter
28. Weighted undirected Stronger weights diameter
29. Weighted directed normalize Stronger weights diameter
30. Weighted undirected normalize Stronger weights diameter
31. Binary directed diameter
32. Binary undirected diameter
33. Weighted directed geodesic distances
34. Weighted undirected geodesic distances
35. Weighted directed normalize geodesic distances
36. Weighted undirected normalize geodesic distances
37. Weighted directed Stronger weights geodesic distances
38. Weighted undirected Stronger weights geodesic distances
39. Weighted directed normalize Stronger weights geodesic distances
40. Weighted undirected normalize Stronger weights geodesic distances
41. Binary directed geodesic distances
42. Binary undirected geodesic distances
43. Centralization index
44. Weighted categorical assortativity
45. Binary categorical assortativity
46. Weighted continuous assortativity
47. Binary continuous assortativity
 
Cédric Sueur
added a research item
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.
Sebastian Sosa Orozco
added an update
Official ANT webpage: http://www.s-sosa.com/ant
 
Sebastian Sosa Orozco
added an update
ANT R package open beta officially started today! Want to test it?
  • On R: devtools::install_github("SebastianSosa/ant")
  • Or download the zip file with the following links:
 
Sebastian Sosa Orozco
added an update
ANT close beta officially started! Thanks to William Hoppitt, DamienFarine , VIncent Vilblanc , Cristian Pasquaretta , Valeria Romano for taking the time to have a look at the package.An open beta will be launched very soon.
Thanks to Ivan Puga-Gonzalez and Cédric Sueur for their help in writing the tutorial and programming.
 
Sebastian Sosa Orozco
added an update
ANT will provide the user with a graphical interface for node network metric computations.
#ANT #R #Rstats #SNA #AnimalSocieties #Network
 
Cédric Sueur
added an update
And the logo ANT (Animal Network Toolkit)!
 
Sebastian Sosa Orozco
added a project goal
How animals interact and develop social relationships in face of sociodemographic and ecological pressures is of great interest. New methodologies, in particular Social Network Analysis (SNA), 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 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- and post-network (node and link permutations); 3) perform statistical permutation tests as correlation test, t-test, General Linear Model, General Linear Mixed Model, deletion simulation, Matrix TauKr correlations , MRQAP. The package is partially coded in C++ using the R package Rcpp for an optimal coding speed. The package gives researchers a workflow from the raw data to the achievement of statistical analyses, allowing for a multilevel approach: from the individual’s position and role within the network, to the identification of interactional patterns, and the study of the overall network properties. Furthermore, ANT also provides a guideline on the SNA techniques used: 1) from the appropriate randomization technique according to the data collected; 2) to the choice, the meaning, the limitations and advantages of the network metrics to apply, 3) and the type of statistical tests to run. The ANT project is multi-collaborative, aiming to provide access to advanced social network analysis techniques and to create new ones that meet researchers’ needs in future versions.