Using the relational event model (REM) to investigate the temporal dynamics of animal social networks

Tranmer, M. , Marcum, C. S., Morton, F. B., Croft, D. P. and de Kort, S. R. (2015) Using the relational event model (REM) to investigate the temporal dynamics of animal social networks. Animal Behaviour, 101, pp. 99-105. (doi:10.1016/j.anbehav.2014.12.005) (PMID:26190856) (PMCID:PMC4502436)

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Abstract

Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula, in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

Item Type:Articles
Additional Information:Work by C.S.M. was supported by the National Institutes of Health Intramural Research Program (Z01HG200335 Koehly, PI). F.B.M thanks Professors Phyllis C. Lee and Hannah M. BuchananSmith for supervising the research and the University of Stirling and Primate Society of Great Britain for funding. Work by D.P.C. was supported by funding from The Leverhulme Trust (RPG-17).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Tranmer, Professor Mark
Authors: Tranmer, M., Marcum, C. S., Morton, F. B., Croft, D. P., and de Kort, S. R.
Subjects:H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
College/School:College of Social Sciences > School of Social and Political Sciences
Journal Name:Animal Behaviour
Publisher:Elsevier
ISSN:0003-3472
Published Online:22 January 2015
Copyright Holders:Copyright © 2015 The Association for the Study of Animal Behaviour
First Published:First published in Animal Behaviour 101: 99-105
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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