Fractional group identification

Wonki Cho, Chang Woo Park

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

We study group identification problems, the objective of which is to classify agents into groups based on individual opinions. Our point of departure from the literature is to allow membership to be fractional, to qualify the extent of belonging. Examining implications of independence of irrelevant opinions, we identify and characterize four nested families of rules. The four families include the weighted-average rules, which are obtained by taking a weighted average of all entries of a problem, and the fractional consent rules, which adapt the consent rules from the binary model to our multinary setup, balancing two principles in group identification, namely liberalism and social consent. Existing characterizations of the one-vote rules, the consent rules, and the liberal rule follow from ours.

Original languageEnglish
Pages (from-to)66-75
Number of pages10
JournalJournal of Mathematical Economics
Volume77
DOIs
Publication statusPublished - 2018 Aug 1

Fingerprint

Fractional
Weighted Average
Identification Problem
Vote
Consent
Balancing
Classify
Binary
Family

Keywords

  • Fractional consent rules
  • Fractional membership
  • Independence of irrelevant opinions
  • Liberal rule
  • Weighted-average rules

ASJC Scopus subject areas

  • Economics and Econometrics
  • Applied Mathematics

Cite this

Fractional group identification. / Cho, Wonki; Park, Chang Woo.

In: Journal of Mathematical Economics, Vol. 77, 01.08.2018, p. 66-75.

Research output: Contribution to journalArticle

Cho, Wonki ; Park, Chang Woo. / Fractional group identification. In: Journal of Mathematical Economics. 2018 ; Vol. 77. pp. 66-75.
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