301. Comparing thematic and search term-based coding in understanding sense of place in survey research.
- Author
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Cotton, Isabel, McWherter, Brooke, Tenbrink, Thora, and Sherren, Kate
- Subjects
SOCIAL impact assessment ,PLACE attachment (Psychology) ,SOCIAL scientists ,THEMATIC analysis ,HUMAN geography ,BIG data - Abstract
Sense of place is a fundamental concept in human geography, yet challenging to measure given its intangibility and idiosyncrasy. Meanwhile, there are increasing opportunities for social scientists to utilize big data and automated approaches to data analysis, albeit with some wariness, but few researchers directly compare automated to manual analysis in the context of sense of place. This study applies two analytical approaches to a survey question on sense of place: semi-automatic search term analysis around semantic fields, and inductive thematic analysis. Results show high agreement between the approaches, with more tangible aspects of place (recreation) better correlated than more abstract concepts (appreciation). Variation mainly relates to the ability of inductive coding to address false negatives, implied meaning, or obscure search terms. This demonstrates the potential value of hybridizing to improve the accuracy of a search term-based approach, and overcome the limitations, such as subjectivities, of one analytical approach. • The research compares search term-based and thematic analysis to understand sense of place. • Tangible aspects of place (such as recreation) agree more than more abstract elements (such as cultural heritage). • We advocate a hybrid coding approach to combine the advantages and overcome the limitations of each approach. • A hybrid approach facilitates use of Big Data as well as deployment in applied fields such as social impact assessment. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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