ArticleProceedings of the National Academy of Sciences of the United States of America2018
Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed, 137 citations in OpenAlex.
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- BeeCam-AprilTag: timing the flight duration of individual honey bees in remote field settings with AprilTag and Raspberry Pi.MethodsX · 2025Article
- Genetic variation influences food-sharing sociability in honey bees.PLoS biology · 2025Article
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- Integrating computer vision and molecular neurobiology to bridge the gap between behavior and the brain.Current opinion in insect science · 2024Review
- Automated entrance monitoring to investigate honey bee foraging trips using open-source wireless platform and fiducial tags.HardwareX · 2024Article
- Collective signalling is shaped by feedbacks between signaller variation, receiver perception and acoustic environment in a simulated communication network.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Beehive scale-free emergent dynamics.Scientific reports · 2024Article
- Susceptible and infectious states for both vector and host in a dynamic pathogen-vector-host system.Proceedings. Biological sciences · 2024Article
- Gut microbiota contribute to variations in honey bee foraging intensity.The ISME journal · 2024Article
- Generation paths of online public opinion impact in public health emergency: a fuzzy-set qualitative comparative analysis based on Chinese data.Frontiers in public health · 2024Article
- Beehive scale-free emergent dynamics.ArXiv · 2023Article
- Constructing temporal networks with bursty activity patterns.Nature communications · 2023Article
- NAPS: Integrating pose estimation and tag-based tracking.Methods in ecology and evolution · 2023Article
- How honeybees respond to heat stress from the individual to colony level.Journal of the Royal Society, Interface · 2023Article
- Spontaneous and information-induced bursting activities in honeybee hives.Scientific reports · 2023Article
- Emergent regulation of ant foraging frequency through a computationally inexpensive forager movement rule.eLife · 2023Article
- Low-distortion information propagation with noise suppression in swarm networks.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior.Scientific reports · 2023Article
- Evidence of Critical Dynamics in Movements of Bees inside a Hive.Entropy (Basel, Switzerland) · 2022Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Social networks mediate the spread of information and disease. The dynamics of spreading depends, among other factors, on the distribution of times between successive contacts in the network. Heavy-tailed (bursty) time distributions are characteristic of human communication networks, including face-to-face contacts and electronic communication via mobile phone calls, email, and internet communities. Burstiness has been cited as a possible cause for slow spreading in these networks relative to a randomized reference network. However, it is not known whether burstiness is an epiphenomenon of human-specific patterns of communication. Moreover, theory predicts that fast, bursty communication networks should also exist. Here, we present a high-throughput technology for automated monitoring of social interactions of individual honeybees and the analysis of a rich and detailed dataset consisting of more than 1.2 million interactions in five honeybee colonies. We find that bees, like humans, also interact in bursts but that spreading is significantly faster than in a randomized reference network and remains so even after an experimental demographic perturbation. Thus, while burstiness may be an intrinsic property of social interactions, it does not always inhibit spreading in real-world communication networks. We anticipate that these results will inform future models of large-scale social organization and information and disease transmission, and may impact health management of threatened honeybee populations.
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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.