A comprehensive framework for automated identification of cultural ecosystem services
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F25%3A43927418" target="_blank" >RIV/62156489:43110/25:43927418 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1016/j.ecoser.2025.101770" target="_blank" >https://doi.org/10.1016/j.ecoser.2025.101770</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ecoser.2025.101770" target="_blank" >10.1016/j.ecoser.2025.101770</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A comprehensive framework for automated identification of cultural ecosystem services
Popis výsledku v původním jazyce
Cultural ecosystem services (CES) represent intangible values, making them inherently challenging to analyze. In this study, we present a framework that combines web scraping, text mining, and statistical analysis to gain deeper insights into how people perceive valuable ecosystems and the benefits they derive from them. A total of 4,760 public reviews were collected from the Google Maps platform using dynamic web scraping techniques. Machine learning-based topic modelling was then applied to identify key themes related to CES in selected national parks and protected areas across the Czech Republic. Finally, we tested the hypothesis that the relative frequency of specific topics varies significantly between locations. The proposed approach proved effective in the automated evaluation of CES and in highlighting the distinctive features of the studied sites.
Název v anglickém jazyce
A comprehensive framework for automated identification of cultural ecosystem services
Popis výsledku anglicky
Cultural ecosystem services (CES) represent intangible values, making them inherently challenging to analyze. In this study, we present a framework that combines web scraping, text mining, and statistical analysis to gain deeper insights into how people perceive valuable ecosystems and the benefits they derive from them. A total of 4,760 public reviews were collected from the Google Maps platform using dynamic web scraping techniques. Machine learning-based topic modelling was then applied to identify key themes related to CES in selected national parks and protected areas across the Czech Republic. Finally, we tested the hypothesis that the relative frequency of specific topics varies significantly between locations. The proposed approach proved effective in the automated evaluation of CES and in highlighting the distinctive features of the studied sites.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10103 - Statistics and probability
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Ecosystem Services
ISSN
2212-0416
e-ISSN
2212-0416
Svazek periodika
75
Číslo periodika v rámci svazku
October
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
12
Strana od-do
101770
Kód UT WoS článku
001566905200001
EID výsledku v databázi Scopus
2-s2.0-105014975530