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Stability of centrality measures in valued networks regarding different actor non-response treatments and macro-network structures

Published online by Cambridge University Press:  30 October 2017

ANJA ŽNIDARŠIČ ,
ANUŠKA FERLIGOJ  and
PATRICK DOREIAN
ANJA ŽNIDARŠIČ
Affiliation:
University of Maribor, Faculty of Organizational Sciences, Kidričeva 55a, 4000 Kranj, Slovenia (e-mail: anja.znidarsic@fov.uni-mb.si)
ANUŠKA FERLIGOJ
Affiliation:
University of Ljubljana, Faculty of Social Sciences, Kardeljeva ploščad 5, 1000 Ljubljana, Slovenia (e-mail: anuska.ferligoj@fdv.uni-lj.si)
PATRICK DOREIAN
Affiliation:
University of Ljubljana, Faculty of Social Sciences, Kardeljeva ploščad 5, 1000 Ljubljana, Slovenia University of Pittsburgh, Department of Sociology, USA (e-mail: pitpat@pitt.edu)
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Abstract

Social network data are prone to errors regardless their source. This paper focuses on missing data due to actor non-response in valued networks. If actors refuse to provide information, all values for outgoing ties are missing. Partially observed incoming ties to non-respondents and all other patterns for ties between members of the network can be used to impute missing outgoing ties. Many centrality measures are used to determine the most prominent actors inside the network. Using treatments for actor non-response enables us to estimate better the centrality scores of all actors regarding their popularity or prominence. Simulations using initial known blockmodel structures based on three most frequently occurring macro-network structures: cohesive subgroups, core-periphery models, and hierarchical structures were used to evaluate the relative merits of the treatments for non-response. The results indicate that the amount of non-respondents, the type of underlying macro-structure, and the employed treatment have an impact on centrality scores. Regardless of the underlying network structure, the median of the 3-nearest neighbors based on incoming ties performs the best. The adequacy (or not) of the other non-response treatments is contingent on the network macro-structure.

Keywords

valued networkactor non-responsemissing dataactor non-response treatmentsblockmodeling structureweighted centrality measures
Type
Research Article
Information
Network Science , Volume 6 , Issue 1 , March 2018 , pp. 1 - 33
Copyright
Copyright © Cambridge University Press 2017 

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