Journal ArticleDOI
Reality mining of animal social systems.
Jens Krause,Stefan Krause,Robert Arlinghaus,Robert Arlinghaus,Ioannis Psorakis,Stephen J. Roberts,Christian Rutz +6 more
TLDR
Important issues concerning the collection of data on the social dynamics of almost entire populations of individuals, and their processing and analysis, are reviewed to identify the most promising approaches in the emerging field of 'reality mining'.Abstract:
The increasing miniaturisation of animal-tracking technology has made it possible to gather exceptionally detailed machine-sensed data on the social dynamics of almost entire populations of individuals, in both terrestrial and aquatic study systems. Here, we review important issues concerning the collection of such data, and their processing and analysis, to identify the most promising approaches in the emerging field of 'reality mining'. Automated technologies can provide data sensing at time intervals small enough to close the gap between social patterns and their underlying processes, providing insights into how social structures arise and change dynamically over different timescales. Especially in conjunction with experimental manipulations, reality mining promises significant advances in basic and applied research on animal social systems.read more
Citations
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Journal ArticleDOI
Constructing, conducting and interpreting animal social network analysis
TL;DR: The under‐exploited potential of experimental manipulations on social networks to address research questions is highlighted, and an overview of methods for quantifying properties of nodes and networks, as well as for testing hypotheses concerning network structure and network processes are provided.
Journal ArticleDOI
Automated image-based tracking and its application in ecology
Anthony I. Dell,John A. Bender,Kristin Branson,Iain D. Couzin,Gonzalo G. de Polavieja,Lucas P. J. J. Noldus,Alfonso Pérez-Escudero,Pietro Perona,Andrew Straw,Martin Wikelski,Martin Wikelski,Ulrich Brose +11 more
TL;DR: Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers.
Journal ArticleDOI
Applications of machine learning in animal behaviour studies
TL;DR: This review aims to introduce animal behaviourists unfamiliar with machine learning (ML) to the promise of these techniques for the analysis of complex behavioural data and illustrate key ML approaches by developing data analytical pipelines for three different case studies that exemplify the types of behavioural and ecological questions ML can address.
Journal ArticleDOI
A guide to null models for animal social network analysis.
TL;DR: It is shown that permutations of the raw observational (or ‘pre‐network’) data consistently account for underlying structure in the generated social network, and thus can reduce both type I and type II error rates.
Journal ArticleDOI
Infectious disease transmission and contact networks in wildlife and livestock
TL;DR: The rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations is described; the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks is discussed; and knowledge gaps in how to collect and analyse contact data are highlighted.
References
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Journal ArticleDOI
How Multirobot Systems Research will Accelerate our Understanding of Social Animal Behavior
Tucker Balch,Frank Dellaert,Adam Feldman,Andrew Guillory,Charles L. Isbell,Zia Khan,Stephen C. Pratt,Andrew Neil Stein,H. Wilde +8 more
TL;DR: The algorithms developed for tracking, recognizing, and learning models of social animal behavior, details of their implementation, and quantitative experimental results using them to study social insects are presented.
Journal ArticleDOI
Social Network Discovery by Mining Spatio-Temporal Events
TL;DR: A model for constructing a social network from events is proposed, and an algorithm is provided that mines these events from the data to establish relationships between pairs of individuals.
Journal ArticleDOI
Determining association networks in social animals: Choosing spatial-temporal criteria and sampling rates
Hamed Haddadi,Andrew J. King,Alison Wills,Damien Fay,J. C. Lowe,A. Jennifer Morton,Stephen Hailes,Alan M. Wilson +7 more
TL;DR: This paper demonstrates how researchers can use experimental and statistical methods to establish spatial and temporal association patterns and thus correctly characterise social networks in both time and space and indicates the need for sampling intervals of less than a minute apart.