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Detecting and quantifying social transmission using network-based diffusion analysis.

Matthew J Hasenjager1, Ellouise Leadbeater1, William Hoppitt1

  • 1Department of Biological Sciences, Royal Holloway University of London, Egham, UK.

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Summary
This summary is machine-generated.

Network-based diffusion analysis (NBDA) helps detect social learning in animal groups by analyzing behavior spread through social networks. This guide provides a framework and practical steps for researchers to effectively apply NBDA.

Keywords:
culturedisease transmissionnetwork-based diffusion analysissocial learningsocial network analysissocial transmission

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Area of Science:

  • Animal behavior
  • Social learning
  • Network analysis

Background:

  • Social learning is widespread in animals, but demonstrating its occurrence in natural settings is difficult.
  • Observational data from freely interacting groups can be used to infer social learning.
  • Network-based diffusion analysis (NBDA) provides a statistical framework to detect social learning from such data.

Purpose of the Study:

  • To provide a comprehensive guide on applying Network-based diffusion analysis (NBDA) for detecting social learning.
  • To explain the mathematical framework and applications of NBDA.
  • To assist researchers in selecting appropriate methods and interpreting results.

Main Methods:

  • Introduces the mathematical framework of NBDA.
  • Guides on selecting social networks and NBDA variants.
  • Details incorporating variables influencing social and asocial learning.
  • Explains interpretation of NBDA model outputs and model selection.

Main Results:

  • Presents NBDA as a robust method for analyzing social learning from observational data.
  • Highlights extensions such as dynamic and multi-network NBDA.
  • Provides practical recommendations and worked examples using the R package 'nbda'.

Conclusions:

  • NBDA is a valuable tool for studying social learning in animal populations.
  • The guide and associated R package facilitate the application of NBDA in research.
  • Further extensions allow for more complex analyses of social information flow.