Crowdsourced text analysis to characterize the U.S. National Parks based on cultural ecosystem services

•We utilized TripAdvisor reviews to analyze CES in 48 U.S. National Parks.•A crowdsourced lexicon was generated to annotate phrases with eight CES.•Based on CES compositions, the parks were categorized into four groups.•Key phrases described points-of-interest and activities at each park level.•Unde...

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Published inLandscape and urban planning Vol. 233; p. 104692
Main Authors Kong, Inhye, Sarmiento, Fausto O., Mu, Lan
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.05.2023
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Online AccessGet full text
ISSN0169-2046
1872-6062
DOI10.1016/j.landurbplan.2023.104692

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Abstract •We utilized TripAdvisor reviews to analyze CES in 48 U.S. National Parks.•A crowdsourced lexicon was generated to annotate phrases with eight CES.•Based on CES compositions, the parks were categorized into four groups.•Key phrases described points-of-interest and activities at each park level.•Understanding CES can assist park management and planning. Perceiving cultural ecosystem services (CES) are subject to physical landscape settings and sociocultural context. However, we still have a limited understanding of multiple CES and how they differ across heterogeneous landscapes. This study aims to identify and compare eight different CES across 48 National Parks in the United States. The study uses TripAdvisor reviews as a source of data and applies text analysis and a crowdsourced lexicon to assign CES for phrasal expressions. We found that the parks can be grouped into four categories based on the composition of CES: (a) Aesthetic, (b) Biological/Spiritual, (c) Recreation/Identity, or (d) Cultural/Educational/Social values. The most commonly used phrases in the reviews correspond to the specific CES group of the park, while describing key attractions and popular activities. The geographic distribution of the parks also revealed spatial autocorrelations depending on the CES group. Overall, the study demonstrates how crowdsourced text analysis can be used to inform data-driven management strategies that promote unique niches for tourism while diversifying conservation agendas.
AbstractList •We utilized TripAdvisor reviews to analyze CES in 48 U.S. National Parks.•A crowdsourced lexicon was generated to annotate phrases with eight CES.•Based on CES compositions, the parks were categorized into four groups.•Key phrases described points-of-interest and activities at each park level.•Understanding CES can assist park management and planning. Perceiving cultural ecosystem services (CES) are subject to physical landscape settings and sociocultural context. However, we still have a limited understanding of multiple CES and how they differ across heterogeneous landscapes. This study aims to identify and compare eight different CES across 48 National Parks in the United States. The study uses TripAdvisor reviews as a source of data and applies text analysis and a crowdsourced lexicon to assign CES for phrasal expressions. We found that the parks can be grouped into four categories based on the composition of CES: (a) Aesthetic, (b) Biological/Spiritual, (c) Recreation/Identity, or (d) Cultural/Educational/Social values. The most commonly used phrases in the reviews correspond to the specific CES group of the park, while describing key attractions and popular activities. The geographic distribution of the parks also revealed spatial autocorrelations depending on the CES group. Overall, the study demonstrates how crowdsourced text analysis can be used to inform data-driven management strategies that promote unique niches for tourism while diversifying conservation agendas.
Perceiving cultural ecosystem services (CES) are subject to physical landscape settings and sociocultural context. However, we still have a limited understanding of multiple CES and how they differ across heterogeneous landscapes. This study aims to identify and compare eight different CES across 48 National Parks in the United States. The study uses TripAdvisor reviews as a source of data and applies text analysis and a crowdsourced lexicon to assign CES for phrasal expressions. We found that the parks can be grouped into four categories based on the composition of CES: (a) Aesthetic, (b) Biological/Spiritual, (c) Recreation/Identity, or (d) Cultural/Educational/Social values. The most commonly used phrases in the reviews correspond to the specific CES group of the park, while describing key attractions and popular activities. The geographic distribution of the parks also revealed spatial autocorrelations depending on the CES group. Overall, the study demonstrates how crowdsourced text analysis can be used to inform data-driven management strategies that promote unique niches for tourism while diversifying conservation agendas.
ArticleNumber 104692
Author Kong, Inhye
Sarmiento, Fausto O.
Mu, Lan
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  year: 2018
  ident: 10.1016/j.landurbplan.2023.104692_b0035
  article-title: Using geo-tagged Instagram posts to reveal landscape values around current and proposed hydroelectric dams and their reservoirs
  publication-title: Landscape and Urban Planning
  doi: 10.1016/j.landurbplan.2017.07.004
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Snippet •We utilized TripAdvisor reviews to analyze CES in 48 U.S. National Parks.•A crowdsourced lexicon was generated to annotate phrases with eight CES.•Based on...
Perceiving cultural ecosystem services (CES) are subject to physical landscape settings and sociocultural context. However, we still have a limited...
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SubjectTerms aesthetics
ecosystems
geographical distribution
Landscape management
landscapes
Online tourism review
Protected areas
recreation
Social media
Text analysis
tourism
Title Crowdsourced text analysis to characterize the U.S. National Parks based on cultural ecosystem services
URI https://dx.doi.org/10.1016/j.landurbplan.2023.104692
https://www.proquest.com/docview/2834250517
Volume 233
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