Analysis of user experience in low-resource languages: A case study of the Uzbek language Google Play reviews
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AARM3FCQB" target="_blank" >RIV/00216208:11320/26:ARM3FCQB - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.ipm.2024.104015" target="_blank" >http://dx.doi.org/10.1016/j.ipm.2024.104015</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ipm.2024.104015" target="_blank" >10.1016/j.ipm.2024.104015</a>
Alternative languages
Result language
angličtina
Original language name
Analysis of user experience in low-resource languages: A case study of the Uzbek language Google Play reviews
Original language description
Understanding user experience is crucial for business success, yet analyzing user reviews in low-resource languages presents significant challenges due to the scarcity of annotated data. To address this gap, we conducted an in-depth analysis of 27,985 Uzbek reviews from the Google Play Store, focusing on the six key aspects of the User Experience Honeycomb model. Our study meticulously annotated these reviews, comprising a total of 43,712 sentences, to assess the sentiment polarity across these six dimensions. To benchmark this task, we propose an integrated framework that leverages pre-trained models along with GCN to capture semantic relationships, thereby enhancing the accuracy of sentiment analysis. Our approach demonstrated superior performance, achieving an absolute improvement of 0.30 in the F1 score for multi-classification tasks and 0.43 for binary classification tasks compared to existing baseline methods. These results underscore the effectiveness of our proposed framework in understanding user experience in low-resource language contexts, offering valuable insights for businesses and researchers alike. © 2024 Elsevier Ltd
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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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
Information Processing and Management
ISSN
0306-4573
e-ISSN
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Volume of the periodical
62
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
104015
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85211156613