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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

"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"

Název v anglickém jazyce

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

Popis výsledku anglicky

"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"

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

—

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

"Landscape and Urban Planning"

ISSN

0169-2046

e-ISSN

—

Svazek periodika

233

Číslo periodika v rámci svazku

2023

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

1-9

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85146564412