Estimating uncertainty and reliability of social network data using Bayesian inference

Royal Society Open Science

Volumn 2, Issue 9, 2015, Pages

  Farine, Damien R ^a,b,c   Strandburg Peshkin, Ariana ^d  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c SMITHSONIAN TROPICAL RESEARCH INSTITUTE   (Panama)

^d PRINCETON UNIVERSITY   (United States)

Author keywords

Bayesian inference; Group living; Interactions; Social network analysis; Social structure; Uncertainty

Indexed keywords

EID: 84954092194     PISSN: None     EISSN: 20545703     Source Type: Journal    
DOI: 10.1098/rsos.150367     Document Type: Article

References (37)

1. 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, 1271-1277. (doi: 10. 1016/ J. Anbehav. 2012. 08. 008).
2. Pinter-Wollman N et al. 2013 The dynamics of animal social networks: analytical, conceptual, and theoretical advances. Behav. Ecol. 25, 242-255. (doi: 10. 1093/beheco/art047).
3. Sih A, Hanser SF, McHugh KA. 2009 Social network theory: new insights and issues for behavioral ecologists. Behav. Ecol. Sociobiol. 63, 975-988. (doi: 10. 1007/S00265-009-0725-6).
4. Wey T, Blumstein DT, ShenW, Jordan F. 2008 Social network analysis of animal behaviour: a promising tool for the study of sociality. Anim. Behav. 75, 333-344. (doi: 10. 1016/J. Anbehav. 2007. 06. 020).
5. Farine DR, Whitehead H. 2015 Constructing, conducting, and interpreting animal social network analysis. J. Anim. Ecol. 84, 1144-1163. (doi: 10. 1111/ 1365-2656. 12418).
6. Formica VA, Wood CW, LarsenWB, Butterfield RE, Augat ME, Hougen HY, Brodie ED. 2012 Fitness consequences of social network position in a wild population of forked fungus beetles (Bolitotherus cornutus). J. Evol. Biol. 25, 130-137. (doi: 10. 1111/j. 1420-9101. 2011. 02411. x).
7. Wey TW, Burger JR, Ebensperger LA, Hayes LD. 2013 Reproductive correlates of social network variation in plurally breeding degus (Octodon degus). Anim. Behav. 85, 1407-1414. (doi: 10. 1016/j. anbehav. 2013. 03. 035).
8. James R, Croft DP, Krause J. 2009 Potential banana skins in animal social network analysis. Behav. Ecol. Sociobiol. 63, 989-997. (doi: 10. 1007/S00265-009-0742-5).
9. Lusseau D, Whitehead H, Gero S. 2008 Incorporating uncertainty into the study of animal social networks. Anim. Behav. 75, 1809-1815. (doi: 10. 1016/ J. Anbehav. 2007. 10. 029).
10. Whitehead H. 2008 Analyzing animal societies. Chicago, IL: University of Chicago Press.
11. Snijders TAB. 2011 Statistical models for social networks. Annu. Rev. Sociol. 37, 131-153. (doi: 10. 1146/annurev. soc. 012809. 102709).
12. Croft DP, James R, Krause J. 2008 Exploring animal social networks. Princeton, NJ: Princeton University Press.
13. Farine DR. 2015 Proximity as a proxy for interactions: issues of scale in social network analysis. Anim. Behav. 104, e1-e5. (doi: 10. 1016/j. anbehav. 2014. 11. 019).
14. Cairns SJ, Schwager SJ. 1987 A comparison of association indexes. Anim. Behav. 35, 1454-1469. (doi: 10. 1016/S0003-3472(87)80018-0).
15. Efron B, Tibshirani RJ. 1994 An introduction to the bootstrap. Boca Raton, FL: Chapman and Hall/CRC.
16. Butts CT. 2003 Network inference, error, and informant (in)accuracy: a Bayesian approach. Soc. Networks 25, 103-140. (doi: 10. 1016/S0378-8733(02) 00038-2).
17. Everitt RG. 2012 Bayesian parameter estimation for latent Markov random fields and social networks. J. Comp. Graph. Stat. 21, 940-960. (doi: 10. 1080/1061 8600. 2012. 687493).
18. Hunter DR, Krivitsky PN, Schweinberger M. 2012 Computational statistical methods for social network models. J. Comp. Graph. Stat. 21, 856-882. (doi: 10. 1080/10618600. 2012. 732921).
19. Whitehead H. 2009 SOCPROG programs: analysing animal social structures. Behav. Ecol. Sociobiol. 63, 765-778. (doi: 10. 1007/S00265-008-0697-Y).
20. Farine DR. 2013 Animal social network inference and permutations for ecologists in R using asnipe. Methods Ecol. Evol. 4, 1187-1194. (doi: 10. 1111/2041-210X. 12121).
21. R Development Core Team. 2013 R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
22. Murphy KP. 2002 Machine learning: a probabilistic perspective. Cambrige, MA: MIT Press.
23. Agresti A. 2002 Categorical data analysis, 2nd edn. Hoboken, NJ: JohnWiley and Sons, Inc.
24. 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, 3055-3066. (doi: 10. 1098/rsif. 2012. 0223).
25. Psorakis I et al. 2015 Inferring social structure from temporal data. Behav. Ecol. Sociobiol. 69, 857-866. (doi: 10. 1007/s00265-015-1906-0).
26. Aplin LM, Farine DR, Morand-Ferron J, Cockburn A, Thornton A, Sheldon BC. 2015 Experimentally induced innovations lead to persistent culture via conformity inwild birds. Nature 518, 538-541. (doi: 10. 1038/nature13998).
27. Aplin LM, Farine DR, Morand-Ferron J, Cole EF, Cockburn A, Sheldon BC. 2013 Individual personalities predict social behaviour in wild networks of great tits (Parus major). Ecol. Lett. 16, 1365-1372. (doi: 10. 1111/ele. 12181).
28. Farine DR, Sheldon BC. 2015 Selection for territory acquisition is modulated by social network structure in a wild songbird. J. Evol. Biol. 28, 547-556. (doi: 10. 1111/jeb. 12587).
29. Franks DW, Ruxton GD, James R. 2010 Sampling animal association networks with the gambit of the group. Behav. Ecol. Sociobiol. 64, 493-503. (doi: 10. 1007/s00265-009-0865-8).
30. Farine DR et al. 2015 The role of social and ecological processes in structuring animal populations: a case study from automated tracking of wild birds. R. Soc. open sci. 2, 150057. (doi: 10. 1098/rsos. 150057).
31. Bejder L, Fletcher D, Brager S. 1998 A method for testing association patterns of social animals. Anim. Behav. 56, 719-725. (doi: 10. 1006/anbe. 1998. 0802).
32. Croft DP, Madden JR, Franks DW, James R. 2011 Hypothesis testing in animal social networks. Trends Ecol. Evol. 26, 502-507. (doi: 10. 1016/J. Tree. 2011. 05. 012).
33. Farine DR. 2014 Measuring phenotypic assortment in animal social networks: weighted associations are more robust than binary edges. Anim. Behav. 89, 141-153. (doi: 10. 1016/j. anbehav. 2014. 01. 001).
34. Whitehead H, Bejder L, Ottensmeyer CA. 2005 Testing association patterns: issues arising and extensions. Anim. Behav. 69, e1-e6. (doi: 10. 1016/j. anbehav. 2004. 11. 004).
35. Blonder B, Wey TW, Dornhaus A, James R, Sih A. 2012 Temporal dynamics and network analysis. Methods Ecol. Evol. 3, 958-972. (doi: 10. 1111/J. 2041-210x. 2012. 00236. X).
36. Hobson EA, Avery ML, Wright TF. 2013 An analytical framework for quantifying and testing patterns of temporal dynamics in social networks. Anim. Behav. 85, 83-96. (doi: 10. 1016/J. Anbehav. 2012. 10. 010).
37. Haddadi H, King AJ, Wills AP, Fay D, Lowe J, Morton AJ, Hailes S, Wilson AM. 2011 Determining association networks in social animals: choosing spatial-temporal criteria and sampling rates. Behav. Ecol. Sociobiol. 65, 1659-1668. (doi: 10. 1007/S00265-011-1193-3).