AI-driven insights into urban agriculture: Using youtube data to promote social resilience and self-sufficiency
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F25%3AA2603ANQ" target="_blank" >RIV/61988987:17310/25:A2603ANQ - isvavai.cz</a>
Result on the web
<a href="https://linkinghub.elsevier.com/retrieve/pii/S2210670725001520" target="_blank" >https://linkinghub.elsevier.com/retrieve/pii/S2210670725001520</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.scs.2025.106275" target="_blank" >10.1016/j.scs.2025.106275</a>
Alternative languages
Result language
angličtina
Original language name
AI-driven insights into urban agriculture: Using youtube data to promote social resilience and self-sufficiency
Original language description
This study leverages YouTube as a rich data source to explore sustainable urban agriculture practices in small and underutilized yard areas. An innovative methodology integrates disparate data into a coherent dataset and employs deep learning techniques to analyze the coherence of visual and audio content. From 29 videos with similar content addressing self-sufficiency, 20,218 samples based on comments and 106,744 instances incorporating likes were selected. Sentiment scores were calculated using an ensemble approach combining Natural Language Processing and Neural Networks to enhance accuracy and reliability. Findings reveal a moderately positive sentiment towards urban agriculture initiatives, with weighted sentiment scores incorporating likes showing slightly higher positivity, though not significantly different in intensity. This comprehensive approach enhances accuracy by considering a larger population while maintaining dataset coherence. The comparison of positive and negative sentiments, along with weighted sentiments, indicates a faster growth in positive attitudes, highlighting an increasing acceptability of urban agriculture practices. These insights underscore the growing popularity of sustainable urban agriculture and the importance of considering weighted sentiment analysis for a nuanced understanding. This study contributes to the promotion of resilient cultivation practices in urban environments, offering valuable implications for policymakers and practitioners aiming to foster sustainable urban planning.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50700 - Social and economic geography
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sustainable Cities and Society
ISSN
2210-6707
e-ISSN
2210-6715
Volume of the periodical
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Issue of the periodical within the volume
1 April 2025
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
17
Pages from-to
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UT code for WoS article
001447978100001
EID of the result in the Scopus database
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