ArticleRoyal Society open science2015
Estimating uncertainty and reliability of social network data using Bayesian inference.
Article in Royal Society open science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 citing papers in PubMed.
- Social and spatial drivers of the multitiered structure of zebra finch social networks.Proceedings. Biological sciences · 2025Article
- Sedative co-medication patterns across frailty states in people with HIV: a network-based study.International journal of clinical pharmacy · 2025Article
- On the accurate computation of expected modularity in probabilistic networks.Scientific reports · 2025Article
- Group traits moderate the relationship between individual social traits and fitness in gorillas.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data.Movement ecology · 2024Article
- Effect of behavioural sampling methods on local and global social network metrics: a case-study of three macaque species.Royal Society open science · 2023Article
- BISoN: A Bayesian Framework for Inference of Social Networks.Methods in ecology and evolution · 2023Article
- Group-level differences in social network structure remain repeatable after accounting for environmental drivers.Royal Society open science · 2023Article
- Changes in social interaction, social relatedness, and friendships in Education Outside the Classroom: A social network analysis.Frontiers in psychology · 2023Article
- Research Paradigm of Network Approaches in Construction Safety and Occupational Health.International journal of environmental research and public health · 2022Review
- A new method for characterising shared space use networks using animal trapping data.Behavioral ecology and sociobiology · 2022Article
- Permutation tests for hypothesis testing with animal social network data: Problems and potential solutions.Methods in ecology and evolution · 2022Article
- A guide to choosing and implementing reference models for social network analysis.Biological reviews of the Cambridge Philosophical Society · 2021Review
- Reconstruction of plant-pollinator networks from observational data.Nature communications · 2021Article
- Influence of number of individuals and observations per individual on a model of community structure.PloS one · 2021Article
- How to make methodological decisions when inferring social networks.Ecology and evolution · 2020Article
- Predictability and variability of association patterns in sooty mangabeys.Behavioral ecology and sociobiology · 2020Article
- Article
- Choosing a sensible cut-off point: assessing the impact of uncertainty in a social network on the performance of NBDA.Primates; journal of primatology · 2019Article
- Personality shapes pair bonding in a wild bird social system.Nature ecology & evolution · 2018Article
Corrections and comments
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Authors and funding
2 authors.
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Abstract
Social network analysis provides a useful lens through which to view the structure of animal societies, and as a result its use is increasingly widespread. One challenge that many studies of animal social networks face is dealing with limited sample sizes, which introduces the potential for a high level of uncertainty in estimating the rates of association or interaction between individuals. We present a method based on Bayesian inference to incorporate uncertainty into network analyses. We test the reliability of this method at capturing both local and global properties of simulated networks, and compare it to a recently suggested method based on bootstrapping. Our results suggest that Bayesian inference can provide useful information about the underlying certainty in an observed network. When networks are well sampled, observed networks approach the real underlying social structure. However, when sampling is sparse, Bayesian inferred networks can provide realistic uncertainty estimates around edge weights. We also suggest a potential method for estimating the reliability of an observed network given the amount of sampling performed. This paper highlights how relatively simple procedures can be used to estimate uncertainty and reliability in studies using animal social network analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.