Date of Award
5-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Parks, Recreation and Tourism Management
Committee Chair/Advisor
Matthew Brownlee
Committee Member
Sonya Sachdeva
Committee Member
Aby Sene-Harper
Committee Member
Lori Dickes
Abstract
Recent advances in technology have increased the ability to access and manipulate large textual datasets. Natural language processing (NLP), the category of machine learning related to analyzing text data, is often used to understand humans. As with any tool or technology, it is important to critically examine how NLP approaches can support scientific advancement. This dissertation critically evaluates the use of NLP and machine learning in the domain of parks, conservation, and outdoor recreation. The dissertation begins with a novel conceptual chapter, which includes a scoping review of big data methods in outdoor recreation and introduces methodological concepts, best practices, and technical aspects like data sources, analysis techniques, and elements related to research design, ethics, and integrity. Then, those ideas are carried through two contrasting studies that incorporate NLP into mixed methods research design. The first study introduces an inductive framework that uses topic modeling to prepare data for qualitative analysis, and applies the framework to understand patterns and meanings in online trail reviews across the United States. The second study deductively explores deliberative democratic theory in the context of U.S. Forest Service environmental planning. Taken together, this dissertation demonstrates how to incorporate NLP intentionally and critically into both data-driven and theory-driven research. Finally, these articles inform discussion of strengths and shortcomings of specific methods and techniques, managing validity and trustworthiness in mixed methods with machine learning, and epistemological tensions.
Recommended Citation
Dagan, Danielle, "Natural Language Processing Methods for Parks, Conservation, and Outdoor Recreation Research" (2024). All Dissertations. 3583.
https://tigerprints.clemson.edu/all_dissertations/3583
Author ORCID Identifier
0000-0001-9748-669X