Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps
This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Goo...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EnPress Publisher, LLC
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/113868/ http://psasir.upm.edu.my/id/eprint/113868/1/113868.pdf |
| _version_ | 1848866344722759680 |
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| author | Li, Le Ismail, Noor Azlin Chong, Choo Wei Sun, Peng Pervin, Mst. Dilara Hossain, Md Shamim |
| author_facet | Li, Le Ismail, Noor Azlin Chong, Choo Wei Sun, Peng Pervin, Mst. Dilara Hossain, Md Shamim |
| author_sort | Li, Le |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context. |
| first_indexed | 2025-11-15T14:19:07Z |
| format | Article |
| id | upm-113868 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:19:07Z |
| publishDate | 2024 |
| publisher | EnPress Publisher, LLC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1138682025-01-13T02:48:38Z http://psasir.upm.edu.my/id/eprint/113868/ Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps Li, Le Ismail, Noor Azlin Chong, Choo Wei Sun, Peng Pervin, Mst. Dilara Hossain, Md Shamim This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context. EnPress Publisher, LLC 2024-07 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/113868/1/113868.pdf Li, Le and Ismail, Noor Azlin and Chong, Choo Wei and Sun, Peng and Pervin, Mst. Dilara and Hossain, Md Shamim (2024) Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps. Journal of Infrastructure, Policy and Development, 8 (7). art. no. 5311. pp. 1-30. ISSN 2572-7923; eISSN: 2572-7931 https://systems.enpress-publisher.com/index.php/jipd/article/view/5311 10.24294/jipd.v8i7.5311 |
| spellingShingle | Li, Le Ismail, Noor Azlin Chong, Choo Wei Sun, Peng Pervin, Mst. Dilara Hossain, Md Shamim Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps |
| title | Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps |
| title_full | Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps |
| title_fullStr | Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps |
| title_full_unstemmed | Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps |
| title_short | Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps |
| title_sort | customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service apps |
| url | http://psasir.upm.edu.my/id/eprint/113868/ http://psasir.upm.edu.my/id/eprint/113868/ http://psasir.upm.edu.my/id/eprint/113868/ http://psasir.upm.edu.my/id/eprint/113868/1/113868.pdf |