The consequences of unidentifiable individuals for the analysis of an animal social network

Silk, Matthew J.; Jackson, Andrew L.; Croft, Darren P.; Colhoun, Kendrew; Bearhop, Stuart

doi:10.1016/j.anbehav.2015.03.005

Cited by 99 publications

(140 citation statements)

References 56 publications

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“…Thus whilst this data cannot be used to make inferences about the social network structure of the entire Sonso community, it can be used to examine predictors of proximity between pairs of chimpanzees and predictors of the size of proximity networks. Recent simulation analysis has shown that valid conclusions can be drawn about individual level social metrics based on a subset of the whole social network (Silk et al, 2015). Distance to the focal chimpanzee and limb injuries could influence the propensity to use gestural communication, and the type of gestural communication used.…”

Section: Methodsmentioning

confidence: 99%

“…For the purposes of this analysis, degree centrality provides a clearer indication of the direct connectedness of focal chimpanzees to conspecifics in the network and the likely costs of maintaining these relationships, rather than also taking into account indirect network connections. Further, recent simulation analysis demonstrated that when only part of a network is sampled, simple measures of centrality such as degree are more reliable than more complex measures of centrality such as betweenness or eigenvector centrality, which are more dependent on accurately measuring network structure (Silk et al, 2015). This is especially the case when the network is relatively small, as the Sonso community of chimpanzees is.…”

Section: Methodsmentioning

confidence: 99%

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Social Brain Hypothesis: Vocal and Gesture Networks of Wild Chimpanzees

Roberts

2016

Front. Psychol.

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A key driver of brain evolution in primates and humans is the cognitive demands arising from managing social relationships. In primates, grooming plays a key role in maintaining these relationships, but the time that can be devoted to grooming is inherently limited. Communication may act as an additional, more time-efficient bonding mechanism to grooming, but how patterns of communication are related to patterns of sociality is still poorly understood. We used social network analysis to examine the associations between close proximity (duration of time spent within 10 m per hour spent in the same party), grooming, vocal communication, and gestural communication (duration of time and frequency of behavior per hour spent within 10 m) in wild chimpanzees. This study examined hypotheses formulated a priori and the results were not corrected for multiple testing. Chimpanzees had differentiated social relationships, with focal chimpanzees maintaining some level of proximity to almost all group members, but directing gestures at and grooming with a smaller number of preferred social partners. Pairs of chimpanzees that had high levels of close proximity had higher rates of grooming. Importantly, higher rates of gestural communication were also positively associated with levels of proximity, and specifically gestures associated with affiliation (greeting, gesture to mutually groom) were related to proximity. Synchronized low-intensity pant-hoots were also positively related to proximity in pairs of chimpanzees. Further, there were differences in the size of individual chimpanzees' proximity networks—the number of social relationships they maintained with others. Focal chimpanzees with larger proximity networks had a higher rate of both synchronized low- intensity pant-hoots and synchronized high-intensity pant-hoots. These results suggest that in addition to grooming, both gestures and synchronized vocalizations may play key roles in allowing chimpanzees to manage a large and differentiated set of social relationships. Gestures may be important in reducing the aggression arising from being in close proximity to others, allowing for proximity to be maintained for longer and facilitating grooming. Vocalizations may allow chimpanzees to communicate with a larger number of recipients than gestures and the synchronized nature of the pant-hoot calls may facilitate social bonding of more numerous social relationships. As group sizes increased through human evolution, both gestures and synchronized vocalizations may have played important roles in bonding social relationships in a more time-efficient manner than grooming.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Social Brain Hypothesis: Vocal and Gesture Networks of Wild Chimpanzees

Roberts

2016

Front. Psychol.

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“…Missing network data thus require a holistic view and our results offer a toolset to help make that view possible. By looking at a wide range of networks, measures and types of missing data, we can offer recommendations and best practices for applied network practitioners (see Silk et al, 2015, who call for just such an analysis). Even better, a researcher faced with a particular set of circumstances (network type, type of missing data, amount of missing data) might use our results to estimate the bias for their measure of interest.…”

Section: Introductionmentioning

confidence: 99%

Network sampling coverage II: The effect of non-random missing data on network measurement

2017

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Missing data is an important, but often ignored, aspect of a network study. Measurement validity is affected by missing data, but the level of bias can be difficult to gauge. Here, we describe the effect of missing data on network measurement across widely different circumstances. In Part I of this study (Smith and Moody, 2013), we explored the effect of measurement bias due to randomly missing nodes. Here, we drop the assumption that data are missing at random: what happens to estimates of key network statistics when central nodes are more/less likely to be missing? We answer this question using a wide range of empirical networks and network measures. We find that bias is worse when more central nodes are missing. With respect to network measures, Bonacich centrality is highly sensitive to the loss of central nodes, while closeness centrality is not; distance and bicomponent size are more affected than triad summary measures and behavioral homophily is more robust than degree-homophily. With respect to types of networks, larger, directed networks tend to be more robust, but the relation is weak. We end the paper with a practical application, showing how researchers can use our results (translated into a publically available java application) to gauge the bias in their own data.

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“…Silk et al . ; Smith, Moody & Morgan ) will be essential for exploring how robust SAOMs are to the kinds of missing data common in ecological rather than sociological data sets.…”

Section: Challenges When Using Saoms To Study Animal Networkmentioning

confidence: 99%

Analysing animal social network dynamics: the potential of stochastic actor‐oriented models

Fisher

Ilany

Silk

et al. 2017

Journal of Animal Ecology

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Summary1. Animals are embedded in dynamically changing networks of relationships with conspecifics. These dynamic networks are fundamental aspects of their environment, creating selection on behaviours and other traits. However, most social network-based approaches in ecology are constrained to considering networks as static, despite several calls for such analyses to become more dynamic.2. There are a number of statistical analyses developed in the social sciences that are increasingly being applied to animal networks, of which stochastic actor-oriented models (SAOMs) are a principal example. SAOMs are a class of individual-based models designed to model transitions in networks between discrete time points, as influenced by network structure and covariates. It is not clear, however, how useful such techniques are to ecologists, and whether they are suited to animal social networks. 3. We review the recent applications of SAOMs to animal networks, outlining findings and assessing the strengths and weaknesses of SAOMs when applied to animal rather than human networks. We go on to highlight the types of ecological and evolutionary processes that SAOMs can be used to study. 4. SAOMs can include effects and covariates for individuals, dyads and populations, which can be constant or variable. This allows for the examination of a wide range of questions of interest to ecologists. However, high-resolution data are required, meaning SAOMs will not be useable in all study systems. It remains unclear how robust SAOMs are to missing data and uncertainty around social relationships. 5. Ultimately, we encourage the careful application of SAOMs in appropriate systems, with dynamic network analyses likely to prove highly informative. Researchers can then extend the basic method to tackle a range of existing questions in ecology and explore novel lines of questioning.

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The consequences of unidentifiable individuals for the analysis of an animal social network

Cited by 99 publications

References 56 publications

Social Brain Hypothesis: Vocal and Gesture Networks of Wild Chimpanzees

Social Brain Hypothesis: Vocal and Gesture Networks of Wild Chimpanzees

Network sampling coverage II: The effect of non-random missing data on network measurement

Analysing animal social network dynamics: the potential of stochastic actor‐oriented models

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