Behavioral Ecology and Sociobiology

, Volume 69, Issue 5, pp 857–866

Inferring social structure from temporal data

  • Ioannis Psorakis
  • Bernhard Voelkl
  • Colin J. Garroway
  • Reinder Radersma
  • Lucy M. Aplin
  • Ross A. Crates
  • Antica Culina
  • Damien R. Farine
  • Josh A. Firth
  • Camilla A. Hinde
  • Lindall R. Kidd
  • Nicole D. Milligan
  • Stephen J. Roberts
  • Brecht Verhelst
  • Ben C. Sheldon
Methods

DOI: 10.1007/s00265-015-1906-0

Cite this article as:
Psorakis, I., Voelkl, B., Garroway, C.J. et al. Behav Ecol Sociobiol (2015) 69: 857. doi:10.1007/s00265-015-1906-0

Abstract

Social network analysis has become a popular tool for characterising the social structure of populations. Animal social networks can be built either by observing individuals and defining links based on the occurrence of specific types of social interactions, or by linking individuals based on observations of physical proximity or group membership, given a certain behavioural activity. The latter approaches of discovering network structure require splitting the temporal observation stream into discrete events given an appropriate time resolution parameter. This process poses several non-trivial problems which have not received adequate attention so far. Here, using data from a study of passive integrated transponder (PIT)-tagged great tits Parus major, we discuss these problems, demonstrate how the choice of the extraction method and the temporal resolution parameter influence the appearance and properties of the retrieved network and suggest a modus operandi that minimises observer bias due to arbitrary parameter choice. Our results have important implications for all studies of social networks where associations are based on spatio-temporal proximity, and more generally for all studies where we seek to uncover the relationships amongst a population of individuals that are observed through a temporal data stream of appearance records.

Keywords

Social networks Group detection Flocks Gathering events Great tits 

Supplementary material

265_2015_1906_MOESM1_ESM.pdf (567 kb)
ESM 1(PDF 566 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Ioannis Psorakis
    • 1
    • 2
  • Bernhard Voelkl
    • 3
  • Colin J. Garroway
    • 3
  • Reinder Radersma
    • 3
  • Lucy M. Aplin
    • 3
  • Ross A. Crates
    • 3
  • Antica Culina
    • 3
  • Damien R. Farine
    • 3
    • 4
    • 5
  • Josh A. Firth
    • 3
  • Camilla A. Hinde
    • 3
    • 6
  • Lindall R. Kidd
    • 3
  • Nicole D. Milligan
    • 3
  • Stephen J. Roberts
    • 1
  • Brecht Verhelst
    • 3
  • Ben C. Sheldon
    • 3
  1. 1.Department of Engineering ScienceUniversity of OxfordOxfordUK
  2. 2.Thought Machine LtdLondonUK
  3. 3.Edward Grey Institute, Department of ZoologyUniversity of OxfordOxfordUK
  4. 4.Department of AnthropologyUniversity of CaliforniaDavisUSA
  5. 5.Smithsonian Tropical Research InstituteAnconPanama
  6. 6.Department of Animal SciencesUniversity of WageningenWageningenThe Netherlands