Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learning
This study investigates the dynamics of user feedback for two prominent mobile language learning applications, Babbel and Duolingo, through the lenses of Dynamic Systems Theory (DST) and Sociocultural Theory (SCT). By employing a mixed-methods approach that integrates sentiment analysis, network ana...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Computer Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcomp.2025.1569058/full |
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| author | Husnat Ahmed Tabssam Saima Akhtar Chattha Muhammad Farooq Javeed Ali Hayat |
| author_facet | Husnat Ahmed Tabssam Saima Akhtar Chattha Muhammad Farooq Javeed Ali Hayat |
| author_sort | Husnat Ahmed Tabssam |
| collection | DOAJ |
| description | This study investigates the dynamics of user feedback for two prominent mobile language learning applications, Babbel and Duolingo, through the lenses of Dynamic Systems Theory (DST) and Sociocultural Theory (SCT). By employing a mixed-methods approach that integrates sentiment analysis, network analysis, and linguistic features analysis, a dataset of 190 user reviews for each application collected from app review platforms has been analysed. The research reveals distinct sentiment clusters, network metrics, and user engagement patterns, highlighting how sociocultural factors and user experiences shape perceptions of app functionality and effectiveness. Findings indicate that Duolingo users predominantly appreciate the gamified elements and simplicity of lessons, while Babbel users emphasize structured methodologies and cultural context. The application of network analysis using Gephi software elucidates the interconnectedness of user sentiments, identifying influential nodes and feedback trends that inform app design and development. This study contributes to the field of applied linguistics by demonstrating the potential of user feedback to enhance the usability and pedagogical efficacy of language learning technologies, ultimately advocating for a more learner-centered approach in the design of educational tools. The insights garnered from this research not only bridge the gap between linguistic theory and technological application but also underscore the importance of integrating user perspectives in the continuous evolution of language learning platforms. |
| format | Article |
| id | doaj-art-b09dcd323a334a9783d1ac5e18e321c6 |
| institution | Kabale University |
| issn | 2624-9898 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computer Science |
| spelling | doaj-art-b09dcd323a334a9783d1ac5e18e321c62025-08-20T03:24:47ZengFrontiers Media S.A.Frontiers in Computer Science2624-98982025-06-01710.3389/fcomp.2025.15690581569058Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learningHusnat Ahmed Tabssam0Saima Akhtar Chattha1Muhammad Farooq Javeed2Ali Hayat3Riphah Institute of Languages and Literature, Riphah International University, Lahore, PakistanDepartment of Humanities, COMSATS University Islamabad, Lahore Campus, Lahore, PakistanDepartment of Language and Literature, The University of Lahore, Lahore, PakistanFaculty of Arts and Sciences, Near East University, Nicosia, CyprusThis study investigates the dynamics of user feedback for two prominent mobile language learning applications, Babbel and Duolingo, through the lenses of Dynamic Systems Theory (DST) and Sociocultural Theory (SCT). By employing a mixed-methods approach that integrates sentiment analysis, network analysis, and linguistic features analysis, a dataset of 190 user reviews for each application collected from app review platforms has been analysed. The research reveals distinct sentiment clusters, network metrics, and user engagement patterns, highlighting how sociocultural factors and user experiences shape perceptions of app functionality and effectiveness. Findings indicate that Duolingo users predominantly appreciate the gamified elements and simplicity of lessons, while Babbel users emphasize structured methodologies and cultural context. The application of network analysis using Gephi software elucidates the interconnectedness of user sentiments, identifying influential nodes and feedback trends that inform app design and development. This study contributes to the field of applied linguistics by demonstrating the potential of user feedback to enhance the usability and pedagogical efficacy of language learning technologies, ultimately advocating for a more learner-centered approach in the design of educational tools. The insights garnered from this research not only bridge the gap between linguistic theory and technological application but also underscore the importance of integrating user perspectives in the continuous evolution of language learning platforms.https://www.frontiersin.org/articles/10.3389/fcomp.2025.1569058/fullmobile language learning applications (MLLAs)sentiment analysisuser feedbackBabbelDuolingo |
| spellingShingle | Husnat Ahmed Tabssam Saima Akhtar Chattha Muhammad Farooq Javeed Ali Hayat Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learning Frontiers in Computer Science mobile language learning applications (MLLAs) sentiment analysis user feedback Babbel Duolingo |
| title | Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learning |
| title_full | Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learning |
| title_fullStr | Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learning |
| title_full_unstemmed | Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learning |
| title_short | Sentiment analysis of user reviews: exploring Duolingo and Babbel in English language learning |
| title_sort | sentiment analysis of user reviews exploring duolingo and babbel in english language learning |
| topic | mobile language learning applications (MLLAs) sentiment analysis user feedback Babbel Duolingo |
| url | https://www.frontiersin.org/articles/10.3389/fcomp.2025.1569058/full |
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