Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks Article Swipe
Tim Gernat
,
Vikyath D. Rao
,
Martin Middendorf
,
Harry Dankowicz
,
Nigel Goldenfeld
,
Gene E. Robinson
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1073/pnas.1713568115
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1073/pnas.1713568115
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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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1073/pnas.1713568115
- https://www.pnas.org/content/pnas/115/7/1433.full.pdf
- OA Status
- hybrid
- Cited By
- 136
- References
- 65
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W2794000792Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1073/pnas.1713568115Digital Object Identifier
- Title
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Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-01-29Full publication date if available
- Authors
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Tim Gernat, Vikyath D. Rao, Martin Middendorf, Harry Dankowicz, Nigel Goldenfeld, Gene E. RobinsonList of authors in order
- Landing page
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https://doi.org/10.1073/pnas.1713568115Publisher landing page
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https://www.pnas.org/content/pnas/115/7/1433.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://www.pnas.org/content/pnas/115/7/1433.full.pdfDirect OA link when available
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Burstiness, Computer science, Evolving networks, Complex network, Computer network, World Wide Web, Network packetTop concepts (fields/topics) attached by OpenAlex
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136Total citation count in OpenAlex
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2025: 10, 2024: 16, 2023: 16, 2022: 17, 2021: 23Per-year citation counts (last 5 years)
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65Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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