A Neuro-Fuzzy Approach to Measuring Attitudes

  • Maria Symeonaki
  • Aggeliki Kazani
  • Catherine Michalopoulou
Chapter
Part of the The Springer Series on Demographic Methods and Population Analysis book series (PSDE, volume 46)

Abstract

The present paper deals with the application of neuro-fuzzy techniques to the measurements of attitudes. The methodology used is illustrated and evaluated on data drawn from a large-scale survey conducted by the National Centre of Social Research of Greece, in order to investigate opinions, attitudes and stereotypes towards the “other” foreigner. The illustration provides a meaningful way of classifying respondents into xenophobic levels, taking also into account other important socio-demographic characteristics, such as age, education, gender, political beliefs, religion practice and the way each question is answered by the respondent. Moreover, the methodology provides a way of classifying respondents whose responses are identified as questionable.

Keywords

Likert scales Attitude measurement Neuro-fuzzy systems 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Maria Symeonaki
    • 1
  • Aggeliki Kazani
    • 1
  • Catherine Michalopoulou
    • 1
  1. 1.Department of Social Policy, School of Political SciencesPanteion University of Social and Political SciencesAthensGreece

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