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      Social preferences and network structure in a population of reef manta rays

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          The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations

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            Is Open Access

            Constructing, conducting and interpreting animal social network analysis

            Summary 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. 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. 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. 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. 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.
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              A comparison of association indices

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                Author and article information

                Journal
                Behavioral Ecology and Sociobiology
                Behav Ecol Sociobiol
                Springer Science and Business Media LLC
                0340-5443
                1432-0762
                August 2019
                August 22 2019
                August 2019
                : 73
                : 8
                Article
                10.1007/s00265-019-2720-x
                13cf9825-02a5-484b-a4c6-3d6531914ef6
                © 2019

                http://www.springer.com/tdm

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