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Inertia in cognitive processes: the case of the COVID-19 vaccine.

Joseph WoelfelEdward L FinkDeborah A CaiKenton AndersonAsa IacobucciHua Wang
Published in: Quality & quantity (2023)
Developments in factor analysis (Spearman in Am J Psychol 15:201-292, 1904); Thurstone in Multiple factor analysis, University of Chicago Press, Chicago, 1947), multidimensional scaling (Torgerson in Theory and methods of scaling, Wiley Hoboken, New Jersey, 1958; Young and Householder in Psychometrika, 3:19-22, 1938), the Galileo model (Woelfel and Fink in The measurement of communication processes: galileo theory and method, Academic Press Cambridge, Massachusetts, 1980), and, more recently, in computer science, artificial intelligence, computational linguistics, network analysis and other disciplines (Woelfel in Qual Quant 54:263-278, 2020) have shown that human cognitive and cultural beliefs and attitudes can be modeled as movement through a high-dimensional non-Euclidean space. This article demonstrates the theoretical and methodological contribution that multidimensional scaling makes to understand attitude change associated with the COVID-19 vaccine.
Keyphrases
  • artificial intelligence
  • coronavirus disease
  • network analysis
  • sars cov
  • deep learning
  • machine learning
  • endothelial cells
  • big data
  • public health
  • mental health
  • respiratory syndrome coronavirus