Obtain network structures from animal GPS telemetry observations and statistically analyse them to assess their adequacy for social network analysis. Methods include pre-network data permutations, bootstrapping techniques to obtain confidence intervals for global and node-level network metrics, and correlation and regression analysis of the local network metrics.
The goal of aniSNA is to provide easy to use functions for the ecologists aiming to perform social network analysis on the animal GPS telemetry data. See Kaur, Ciuti, Reinking, et al. (2024) and Kaur, Ciuti, Ossi, et al. (2024) for details.
Kaur, Prabhleen, Simone Ciuti, Federico Ossi, Francesca Cagnacci, Nicolas Morellet, Anne Loison, Kamal Atmeh, et al. 2024. “A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data.” Movement Ecology 12 (1). https://doi.org/10.1186/s40462-024-00494-6.
Kaur, Prabhleen, Simone Ciuti, Adele K. Reinking, Jeffrey L. Beck, and Michael Salter-Townshend. 2024. “aniSNA : An R package to assess bias and uncertainty in social networks obtained from animals sampled via direct observations or satellite telemetry.” bioRxiv (Cold Spring Harbor Laboratory), May. https://doi.org/10.1101/2024.05.10.593659.