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A foundation for developing a methodology for social network sampling

A foundation for developing a methodology for social network sampling
A foundation for developing a methodology for social network sampling
Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network.
0340-5443
1079-1088
Franks, D.W.
2e61b255-fef7-4e14-89d2-78bb4b7b9051
James, R.
b2bf9dc8-4cb2-41cf-b77c-6b042856f60f
Noble, J.
440f07ba-dbb8-4d66-b969-36cde4e3b764
Ruxton, G.D.
ae478bac-9e80-4c63-b41c-fb5e8c705877
Franks, D.W.
2e61b255-fef7-4e14-89d2-78bb4b7b9051
James, R.
b2bf9dc8-4cb2-41cf-b77c-6b042856f60f
Noble, J.
440f07ba-dbb8-4d66-b969-36cde4e3b764
Ruxton, G.D.
ae478bac-9e80-4c63-b41c-fb5e8c705877

Franks, D.W., James, R., Noble, J. and Ruxton, G.D. (2009) A foundation for developing a methodology for social network sampling. Behavioral Ecology and Sociobiology, 63 (7), 1079-1088. (doi:10.1007/s00265-009-0729-2).

Record type: Article

Abstract

Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network.

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e-pub ahead of print date: 2 April 2009
Published date: 1 May 2009
Organisations: Agents, Interactions & Complexity

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Local EPrints ID: 265231
URI: http://eprints.soton.ac.uk/id/eprint/265231
ISSN: 0340-5443
PURE UUID: 2f745bb1-a24f-4a3b-ac6d-677eee1b612c

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Date deposited: 29 Feb 2008 16:05
Last modified: 09 Sep 2019 18:54

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