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J Anim Ecol. 2015 Sep;84(5):1144-63. doi: 10.1111/1365-2656.12418. Epub 2015 Aug 11.

Constructing, conducting and interpreting animal social network analysis.

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Department of Zoology, Edward Grey Institute of Field Ornithology, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK.
Department of Anthropology (Evolutionary), University of California Davis, 1 Shields Avenue, Davis, CA, 95616, USA.
Smithsonian Tropical Research Institute, Ancon, Panama.
Department of Biology, Dalhousie University, 1355 Oxford St, Halifax, NS, Canada, B3H 4J1.


1. Animal social networks are descriptions of social structure which, aside from their intrinsic interest for understanding sociality, can have significant bearing across many fields of biology. 2. Network analysis provides a flexible toolbox for testing a broad range of hypotheses, and for describing the social system of species or populations in a quantitative and comparable manner. However, it requires careful consideration of underlying assumptions, in particular differentiating real from observed networks and controlling for inherent biases that are common in social data. 3. We provide a practical guide for using this framework to analyse animal social systems and test hypotheses. First, we discuss key considerations when defining nodes and edges, and when designing methods for collecting data. We discuss different approaches for inferring social networks from these data and displaying them. We then provide an overview of methods for quantifying properties of nodes and networks, as well as for testing hypotheses concerning network structure and network processes. Finally, we provide information about assessing the power and accuracy of an observed network. 4. Alongside this manuscript, we provide appendices containing background information on common programming routines and worked examples of how to perform network analysis using the r programming language. 5. We conclude by discussing some of the major current challenges in social network analysis and interesting future directions. In particular, we highlight the under-exploited potential of experimental manipulations on social networks to address research questions.


fission-fusion dynamics; group living; methods; social behaviour; social dynamics; social network analysis; social organisation

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