2015
DOI: 10.1007/s00265-015-1883-3
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Time is of the essence: an application of a relational event model for animal social networks

Abstract: Understanding how animal social relationships are created, maintained and severed has ecological and evolutionary significance. Animal social relationships are inferred from observations of interactions between animals; the pattern of interaction over time indicates the existence (or absence) of a social relationship. Autonomous behavioural recording technologies are increasingly being used to collect continuous interaction data on animal associations. However, continuous data sequences are typically aggregate… Show more

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Cited by 19 publications
(13 citation statements)
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“…Repeated patterns of shorter, fleeting encounters can suggest coming together for reassurance or reinforcing familiar relationships, whereas short encounters that are not repeated can indicate agonistic encounters, such as fighting and pushing followed by avoidance. Such encounter patterns are decipherable from proximity logger data when combined with additional analyzes that take into account events as a time series (Patison et al, 2015).…”
Section: Discussionmentioning
confidence: 99%
“…Repeated patterns of shorter, fleeting encounters can suggest coming together for reassurance or reinforcing familiar relationships, whereas short encounters that are not repeated can indicate agonistic encounters, such as fighting and pushing followed by avoidance. Such encounter patterns are decipherable from proximity logger data when combined with additional analyzes that take into account events as a time series (Patison et al, 2015).…”
Section: Discussionmentioning
confidence: 99%
“…To date, several studies have characterized social networks in cattle, using association networks based on spatial proximity data [ (12,(38)(39)(40)(41)(42)(43)(44)(45)(46)]. Although very valuable, association networks only provide information based on potential contacts or relations.…”
Section: Introductionmentioning
confidence: 99%
“…Within SNA, the dynamic analysis of animal social networks has also started to receive more focus (Blonder et al ., ; Pinter‐Wollman et al ., ). There is an array of techniques developed in SNA for the dynamic analysis of networks, which incorporate individual‐ and network‐level influences on changes in social associates and other individual traits, such as temporal exponential random graph models (Hanneke et al ., ; Krivitsky & Handcock, ), stochastic actor‐orientated models (Steglich et al ., ; Fisher et al ., ) and relational event models (Patison et al ., ; Tranmer et al ., ), the latter two allowing the explicit modelling of network structure–trait codynamics. Integrating such explicitly dynamic models with models for evolutionary change in populations of socially interacting individuals (outlined above) may give us a better appreciation of how dynamic changes in individual behaviour, the social environment and ecological and evolutionary processes related to these such as selection are causally linked.…”
Section: The Social Environment As a Dynamic Processmentioning
confidence: 99%