Automated Name Selection for the Network Scale-Up Method

Adrià Fenoy Barceló*, Michal Jan Bojanowski ., Miranda Jessica Lubbers

*Corresponding author for this work

Research output: Working paperPreprint

Abstract

The distribution of the number of acquaintances among members of a society is a relevant featureof its social structure. Furthermore, the number of acquaintances (or “degree”) is used for esti-mating other societal features, such as the size of hard-to-count subpopulations or social cohesion.To estimate the degree, the Network Scale-Up Method (NSUM) asks survey respondents aboutthe number of people they know with a set of first names for which name statistics are available.For this method to be precise, a set of names needs to be selected for the survey that jointly rep-resent the population on a smaller scale in terms of relevant traits such as gender or age. Findingthe optimal set of names is a combinatorial problem for which this paper provides a solution ap-proach. The approach can serve other NSUM users, and can be applied to any population forwhich name statistics distributed over different categories are available. We empirically show thatour approach successfully provides subsets of names replicating the population distribution forsix countries with very different name statistics
Original languageEnglish
PublisherField Methods
Pages1-16
Number of pages16
DOIs
Publication statusPublished - 11 Feb 2023

Keywords

  • network scale-up method
  • social networks
  • acquaintanceship volume
  • combinatorial optimization

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