Comparing thematic and search term-based coding in understanding sense of place in survey research

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Comparing thematic and search term-based coding in understanding sense of place in survey research. / Cotton, Isabel; McWherter, Brooke; Tenbrink, Thora et al.
In: Journal of Environmental Psychology, Vol. 96, 102339, 06.2024.

Research output: Contribution to journalArticlepeer-review

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Cotton, I., McWherter, B., Tenbrink, T., & Sherren, K. (2024). Comparing thematic and search term-based coding in understanding sense of place in survey research. Journal of Environmental Psychology, 96, Article 102339. https://doi.org/10.1016/j.jenvp.2024.102339

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Cotton I, McWherter B, Tenbrink T, Sherren K. Comparing thematic and search term-based coding in understanding sense of place in survey research. Journal of Environmental Psychology. 2024 Jun;96:102339. Epub 2024 May 31. doi: 10.1016/j.jenvp.2024.102339

Author

Cotton, Isabel ; McWherter, Brooke ; Tenbrink, Thora et al. / Comparing thematic and search term-based coding in understanding sense of place in survey research. In: Journal of Environmental Psychology. 2024 ; Vol. 96.

RIS

TY - JOUR

T1 - Comparing thematic and search term-based coding in understanding sense of place in survey research

AU - Cotton, Isabel

AU - McWherter, Brooke

AU - Tenbrink, Thora

AU - Sherren, Kate

PY - 2024/6

Y1 - 2024/6

N2 - 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.

AB - 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.

U2 - 10.1016/j.jenvp.2024.102339

DO - 10.1016/j.jenvp.2024.102339

M3 - Article

VL - 96

JO - Journal of Environmental Psychology

JF - Journal of Environmental Psychology

SN - 0272-4944

M1 - 102339

ER -