Investigation of conceptual networks related to climate change among inhabitants: A case study in Eastern Hungarian settlements with word association method

Kiss Emőke (), Fazekas István () and Balla Dániel ()
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Kiss Emőke: PhD Student, University of Debrecen, Department of Landscape Protection and Environmental Geography, Hungary
Fazekas István: Senior lecturer, University of Debrecen, Department of Landscape Protection and Environmental Geography, Hungary
Balla Dániel: Senior lecturer, University of Debrecen, Department of Data Science and Visualization, Hungary

Eastern European Countryside, 2021, vol. 27, issue 1, 147-178

Abstract: In this study, the word association method was applied in relation to municipalities in Eastern Hungary (Hajdú-Bihar county), where the Sustainable Energy and Climate Action Plan (SECAP) already exists, and where the SECAP has not yet been introduced. In addition to the six municipalities examined, Debrecen, a county seat with the SECAP, was also included in the survey. The aim was to explore the conceptual networks related to climate change and the strength of the relationship between the stimulus word and the associated concepts. The associations representing a common meaning were categorised. The results show that the distribution of conceptual networks and that of categories related to climate change exhibit a similar picture in the group of municipalities with (3 villages) and without the SECAP (3 villages), although significant differences were found when the settlements were examined separately (7 municipalities). Studying the distribution of categories by demographic groups, it was found that educational attainment determines, to the greatest extent, the answers.

Keywords: climate change; questionnaire survey; conceptual network; word associations; SECAP; Hajdú-Bihar County; demography; educational level (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:eaeuco:v:27:y:2021:i:1:p:147-178:n:5

DOI: 10.12775/eec.2021.006

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