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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A5E7FC2F2" target="_blank" >RIV/00216208:11320/23:5E7FC2F2 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146564412&doi=10.1016%2fj.landurbplan.2023.104692&partnerID=40&md5=b6ed793ab52ea576e73138d59f541fa8" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146564412&doi=10.1016%2fj.landurbplan.2023.104692&partnerID=40&md5=b6ed793ab52ea576e73138d59f541fa8</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.landurbplan.2023.104692" target="_blank" >10.1016/j.landurbplan.2023.104692</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    "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. © 2023"

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    "Landscape and Urban Planning"

  • ISSN

    0169-2046

  • e-ISSN

  • Volume of the periodical

    233

  • Issue of the periodical within the volume

    2023

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    9

  • Pages from-to

    1-9

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85146564412