A machine learning model of cultural change: Role of prosociality, political attitudes, and Protestant work ethic

Abhishek Sheetal, Krishna Savani (Corresponding Author)

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)

Abstract

What attitudes, values, and beliefs serve as key markers of cultural change? To answer this question, we examined 221,485 respondents from the World Values Survey, a multiwavecross-country survey of people’s attitudes, values, and beliefs. We trained a machine learningmodel to classify respondents into seven waves (i.e., periods). Once trained, the machinelearning model identified a separate group of 24,611 respondents’ wave with a balanced accuracyof 77%. We then queried the model to identify the attitudes, values, and beliefs thatcontributed the most to its classification decisions, and therefore, served as markers of culturalchange. These included religiosity, social attitudes, political attitudes, independence,life satisfaction, Protestant work ethic, and prosociality. Although past research in culturalchange has discussed decreasing religiosity and increasing liberalism and independence, ithas not yet identified Protestant work ethic, political orientation, and prosociality as valuesrelevant to cultural change. Thus, the current research points to new directions for futureresearch on cultural change that might not be evident from either a deductive or an inductiveapproach.

Original languageEnglish
Pages (from-to)997-1012
Number of pages16
JournalAmerican Psychologist
Volume76
Issue number6
DOIs
Publication statusPublished - 2021
Externally publishedYes

Keywords

  • Cultural change
  • Gradient boosting
  • Machine learning
  • World values survey

ASJC Scopus subject areas

  • General Psychology

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