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

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. This research illustrates that the abductive approach of machine learning, whichfocuses on the most likely explanations for an outcome, can help generate novel insights