2012
DOI: 10.1098/rsif.2012.0223
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Inferring social network structure in ecological systems from spatio-temporal data streams

Abstract: We propose a methodology for extracting social network structure from spatio-temporal datasets that describe timestamped occurrences of individuals. Our approach identifies temporal regions of dense agent activity and links are drawn between individuals based on their cooccurrences across these 'gathering events'. The statistical significance of these connections is then tested against an appropriate null model. Such a framework allows us to exploit the wealth of analytical and computational tools of network a… Show more

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Cited by 160 publications
(187 citation statements)
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“…It is difficult to determine the cause of this difference with our data. Great Tits in this system are socially monogamous and there is evidence that pair bonds are, to a degree, maintained across the NBS (Psorakis et al 2012). Thus, social tendencies during the NBS may then be responsible for this difference.…”
Section: Discussionmentioning
confidence: 99%
“…It is difficult to determine the cause of this difference with our data. Great Tits in this system are socially monogamous and there is evidence that pair bonds are, to a degree, maintained across the NBS (Psorakis et al 2012). Thus, social tendencies during the NBS may then be responsible for this difference.…”
Section: Discussionmentioning
confidence: 99%
“…However, studies of natural or semi-natural populations have become sufficiently sophisticated to generate this type of data. The application of recent technological advancement, such as complex visual recording systems [55,56], as well as proximity loggers that allow the recording of interactions between individuals remotely [57][58][59] and, importantly, also allow the inference of specific behavioural interactions [60], may facilitate obtaining such detailed interaction patterns in species where such observations may have before been unfeasible in experimental and natural populations. Furthermore, experimental studies using semi-natural populations combined with network data will provide an opportunity to measure with exceptional accuracy the pattern of interactions, and help develop an understanding of how fine-scale assortment patterns may affect our measurement of selection using standard techniques.…”
Section: Discussionmentioning
confidence: 99%
“…gambit of the group approach [33]). We used networks constructed using the Gaussian mixture model for event streams (GMMEvent) method [34] to identify gathering events (representing feeding flocks) from the data collected on loggers. The method has been shown to be a robust way to derive social networks from spatio-temporal data streams of co-occurrences of individuals [35].…”
Section: (C) Methods To Describe the Winter Social Environmentmentioning
confidence: 99%