Measuring the fuzziness of human thoughts

An application of fuzzy sets to sociological research

Bibliographic Data

ID10142417
AuthorsShaomin Li (0000-0002-7296-084X, Princeton University, corresponding author)
Year1989
Volume14
Issue1
Pages67-84
Publication date1989-01-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Mathematical Sociology (JOURNAL)
Journal identifiersISSN: 0022-250X • E-ISSN: 1545-5874
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/0022250x.1989.9990044
OpenAlexW1988975410
LanguageEN
Citations received2
References cited1

Conventionally, sociologists measure the membership of an individual to a group by a “0 or 1” characteristic function. But when the definition of that group is fuzzy and an individual is neither a full member nor a nonmember, this dichotomous characteristic function may distort the reality. Instead of the “0 or 1” characteristic function by classical set theory, fuzzy set theory introduces a membership function which is a gradation from 0 to 1 to measure the degree to which an object (an individual) belongs to a concept (a group). Based on the rationale of fuzzy set theory, we suggest some new methods of data collection and analysis. Among several noteworthy findings, two points are emphasized: 1) the fuzzy set is an appropriate way of measuring the fuzziness of human thought; and 2) it allows one to relax the conventional assumption that all individuals have identical distributions and deviations around their means

Data mining · Function (biology · Fuzzy classification · Fuzzy logic · Fuzzy mathematics · Fuzzy measure theory · Fuzzy number · Fuzzy set · Mathematical economics · Measure (data warehouse · Membership function · Object (grammar · Set (abstract data type · Type-2 fuzzy sets and systems · Artificial Intelligence · Computer Science · Fuzzy Systems and Optimization · Mathematics · Multi-Criteria Decision Making

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