A Neuro-Fuzzy Approach to Measuring Attitudes
Maria Symeonaki (),
Aggeliki Kazani and
Catherine Michalopoulou ()
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Maria Symeonaki: Panteion University of Social and Political Sciences, Department of Social Policy, School of Political Sciences
Aggeliki Kazani: Panteion University of Social and Political Sciences, Department of Social Policy, School of Political Sciences
Catherine Michalopoulou: Panteion University of Social and Political Sciences, Department of Social Policy, School of Political Sciences
Chapter Chapter 15 in Demography and Health Issues, 2018, pp 169-181 from Springer
Abstract:
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 (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-319-76002-5_15
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DOI: 10.1007/978-3-319-76002-5_15
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