Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data

Abstract

1. In the 4.5 decades since Altmann (1974) published her seminal paper on the methods for the observational study of behaviour, automated detection and analysis of social interaction networks have fundamentally transformed the ways that ecologists study social behaviour. 2. Methodological developments for collecting data remotely on social behaviour involve indirect inference of associations, direct recordings of interactions and machine vision. 3. These recent technological advances are improving the scale and resolution with which we can dissect interactions among animals. They are also revealing new intricacies of animal social interactions at spatial and temporal resolutions as well as in ecological contexts that have been hidden from humans, making the unwatchable seeable. 4. We first outline how these technological applications are permitting researchers to collect exquisitely detailed information with little observer bias. We further recognize new emerging challenges from these new reality-mining approaches. 5. While technological advances in automating data collection and its analysis are moving at an unprecedented rate, we urge ecologists to thoughtfully combine these new tools with classic behavioural and ecological monitoring methods to place our understanding of animal social networks within fundamental biological contexts.

Accuracy and Precision of Social Relationship Indices

“…Scan sampling or all occurrence and ad libitum sampling (Altmann, 1974) could potentially circumvent this problem of lost data, but this would need a rethinking of how to calculate interaction rates and design studies using these observation methods (Canteloup et al, 2020). With new technological solutions and electronic data collection methods, scan samples and ad libitum data collection are becoming simpler to implement (Smith & Pinter-Wollman, 2020; Van Der Marel et al, 2021).…”

Quantifying the influence of space on social group structure

“…These might be a fixed resource location (where the resource is abundant enough that it is unnecessary to attempt to exclude others) or a shared shelter. Such locations are often used to record data in empirical network studies (Smith & Pinter-Wollman, 2020). For each of our “true” networks we then generated 5000 meeting events between pairs of individuals.…”

Animal social networks: Towards an integrative framework embedding social interactions, space and time

“…For example, Bejder, Fletcher, and Bräger (1998) proposed advanced permutation techniques to examine spatial associations between individuals, and Croft, James, and Krause (2008) together with Whitehead (2008) aggregated most of our knowledge on the study of animal sociality in their seminal books. The growth in the popularity of social network analysis in animal behaviour and ecology has been favoured by methodological advances (Whitehead, 2008), and automated monitoring techniques (Smith & Pinter‐Wollman, 2020) have also played a significant role by scaling up research questions to new and previously intractable species and systems. Using these tools for data collection and analysis has further engaged a lively community of researchers that, together, have contributed a near constant refinement and evolution of social network analysis methods and its application to animals.…”

“…The miniaturisation of biologging devices now enable the study of a wider variety of organisms, from insects to cetaceans (Börger et al., 2020). Biologging provides access to new data sources, using less invasive methods and continuous collection, considerably expanding our knowledge of how animals and groups behave in the wild (Smith & Pinter‐Wollman, 2020). These advances, however, have led to a substantial methodological shift in network construction and analysis (Godfrey, Ansari, Gardner, Farine, & Bull, 2014; Spiegel, Leu, Sih, & Bull, 2016).…”