Behavioral Ecology and Sociobiology

, Volume 69, Issue 5, pp 857–866 | Cite as

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

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 

Notes

Acknowledgements

We thank J. Howe, T. Wilkin, S. Evans, A. Hinks and A. Grabowska for assistance in the field and three anonymous reviewers for valuable comments on the manuscript. This research was funded by an ERC grant to BCS (AdG 250164) and a Microsoft Research Grant to IP. LMA was also funded by an Australian Postgraduate Award and by an International Alliance of Research Universities travel grant.

Ethical standards

All authors declare that the present study complies with the current laws in the UK.

Supplementary material

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

References

  1. Aplin LM, Farine DR, Morand-Feron J, Cole EF, Cockburn A, Sheldon BC (2013) Individual personalities predict social behaviour in wild networks of great tits (Parus major). Ecol Lett 16:1365–1372CrossRefPubMedGoogle Scholar
  2. Barthelemy M, Barrat A, Pastor-Satorras R, Vespignani A (2005) Characterization and modeling of weighted networks. Physica A 346:34–43CrossRefGoogle Scholar
  3. Beijder L, Fletcher D, Brager S (1998) A method for testing association patterns of social animals. Anim Behav 56:719–725CrossRefGoogle Scholar
  4. Cairns SJ, Schwager SJ (1987) A comparison of association indices. Anim Behav 35:1454–1469CrossRefGoogle Scholar
  5. Croft DP, James R, Krause J (2008) Exploring animal social networks. Princeton University Press, PrincetonCrossRefGoogle Scholar
  6. Danon L, Diaz-Guilera A, Duch J, Arenas A (2005) Comparing community structure identification. J Stat Mech-Theory Exp 09, P09008Google Scholar
  7. Farine DR, Garroway CJ, Sheldon BC (2012) Social network analysis of mixed-species flocks: exploring the structure and evolution of interspecific social behaviour. Anim Behav 84:1271–1277CrossRefGoogle Scholar
  8. Franks DW, Ruxton GD, James R (2010) Sampling animal association networks with the gambit of the group. Behav Ecol Sociobiol 64:493–503CrossRefGoogle Scholar
  9. Freeman LC (1979) Centrality in social networks. I: conceptual clarification. Soc Networks 1:215–239CrossRefGoogle Scholar
  10. Garroway CJ, Radersma R, Hinde CA (2015) Perspectives on social network analyses of bird populations. In: Krause J, Croft DP, James R (eds) Animal social networks: perspectives and challenges. Oxford University Press, Oxford, pp 171–183Google Scholar
  11. Gibbons JW, Andrews KM (2004) PIT tagging: simple technology at its best. Bioscience 54:447–454CrossRefGoogle Scholar
  12. Ginsberg JR, Young TP (1992) Measuring associations between individuals or groups in behavioural studies. Anim Behav 44:377–379CrossRefGoogle Scholar
  13. Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99:7821–7826CrossRefPubMedCentralPubMedGoogle Scholar
  14. Gossler A (1993) The great tit. Hamlin, LondonGoogle Scholar
  15. Hinde R (1952) The behaviour of the great tit (Parus major) and some other related species. Behav Suppl 2:1–201Google Scholar
  16. James R, Croft DP, Krause J (2009) Potential banana skins in animal social network analysis. Behav Ecol Sociobiol 63:989–997CrossRefGoogle Scholar
  17. Krause J, Krause S, Arlinghaus R, Psorakis I, Roberts S, Rutz C (2013) Reality mining of animal social systems. Trends Ecol Evol 28:541–551CrossRefPubMedGoogle Scholar
  18. Lahti K, Koivula K, Orell M (1997) Dominance, daily activity and winter survival in willow tits: detrimental cost of long working hours? Behaviour 134:921–939CrossRefGoogle Scholar
  19. Newman MEJ (2010) Networks: an introduction. Oxford University Press, OxfordCrossRefGoogle Scholar
  20. Perrins CM (1979) British tits. Collins, LondonGoogle Scholar
  21. Psorakis I, Roberts SJ, Rezek I, Sheldon BC (2012) Inferring social network structure in ecological systems from spatio-temporal data streams. J R Soc Interface 9:3055–3066CrossRefPubMedCentralPubMedGoogle Scholar
  22. Rutz C, Burns ZT, James R, Ismar SMH, Burt J, Otis B, Bowen J, St Clair JJH (2012) Automated mapping of social networks in wild birds. Curr Biol 22:R669–R671CrossRefPubMedGoogle Scholar
  23. Saitou T (1978) Ecological study of social organization in the great tit Parus major L. I. Basic structure of winter flock. Jpn J Ecol 28:199–214Google Scholar
  24. Smyth B, Nebel S (2013) Passive integrated transponder (PIT) tags in the study of animal movement. Nat Educ Knowl 4:3Google Scholar
  25. Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  26. Watts DJ (1999) Small worlds: the dynamics of networks between order and randomness. Princeton University Press, PrincetonGoogle Scholar
  27. Whitehead H (2008) Analyzing animal societies. The University of Chicago Press, ChicagoCrossRefGoogle Scholar
  28. Whitehead H, Dufault S (1999) Techniques for analyzing vertebrate social structure using identified individuals: review and recommendations. Adv Stud Behav 28:33–74CrossRefGoogle Scholar
  29. Wilson EO (1975) Sociobiology: the new synthesis. Harvard University Press, CambridgeGoogle Scholar

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

Personalised recommendations