Measuring phenotypic assortment in animal social networks: weighted associations are more robust than binary edges
By Damien Farine. 2014
222 citations recorded by the source corpus.
Subfields: Ecology, Evolution, Behavior and Systematics, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/88fbf632e8c162e798e5288dd0b848737267c918
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In Ecology, Evolution, Behavior and Systematics
In Sociology and Political Science
- E. Vander Wal
- Q. Webber
- Damien Farine
- Hal Whitehead
- A. Maldonado‐Chaparro
- Peng He
- Tina W. Wey
- Andrew Sih
Citations in the corpus
- The role of habitat configuration in shaping social structure: a gap in studies of animal social complexity (2019, methodology): “…network density, (2) mean non-zero edge weight, (3) mean network assortativity in terms of the ID of the patch in which individuals are initiated (calculated using the R package ‘assortnet’; Farine 2014) and (4) mean network modularity (calculated with R package ‘igraph’; Csardi and Nepusz 2006).”
- Trends and perspectives on the use of animal social network analysis in behavioural ecology: a bibliometric approach (2019, methodology): “Until the advent of open access software and relatively easy-to-use social network R packages (e.g. Cs ardi & Nepusz, 2006; Farine, 2013, 2014), our findings suggest the social network subdiscipline went through some degree of methodological disarray.”
- Environment modulates population social structure: Experimental evidence from replicated social networks of wild lizards (2016, methodology): “We calculated assortativity by sex for each weekly network, a measure of whether associations were typically between individuals of the same or different sex, using the R package assortnet (Farine, 2014).”
- Constructing, conducting and interpreting animal social network analysis (2015, background): “Further, it relies on the assumption that the observed network is a strong representation of the true network (Croft et al. 2011b), and has the potential for much higher rates of type I and type II errors than randomizations based on shuffling the data stream (Farine 2014).”