Aspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industry
Yazarlar (3)
Doç. Dr. Ayşegül ACAR Karabük Üniversitesi, Türkiye
Doç. Dr. Burak TÜRTEN Karabük Üniversitesi, Türkiye
Doç. Dr. Ersin Diker Gümüşhane Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (ESCI dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Journal of Quality Assurance in Hospitality and Tourism | ||
| Dergi ISSN | 1528-008X Dergi Bilgileri (2024) | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | Türkçe | Basım Tarihi | 08-2024 |
| Cilt / Sayı / Sayfa | 27 / 5 / 994–1019 | DOI | 10.1080/1528008X.2024.2386590 |
| Makale Linki | https://doi.org/10.1080/1528008X.2024.2386590 | ||
| UAK Araştırma Alanları |
İletişim Araştırmaları
Dijital İletişim
Yeni İletişim Teknolojileri
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| Özet |
| Service robots are becoming more prevalent in the service industry, yet the impact they have on customer experiences is not well-documented. This study identified consumer emotions toward service robots in hotels and restaurants, focusing on how specific attributes of these robots affect consumer emotions. Furthermore, it explored which countries generate the most comments on these service robot attributes and the nature of consumer emotions within these regions. Utilizing sentiment analysis, the study examined 52,513 English-language tweets about hotel and restaurant service robots. Additionally, logistic regression analysis helped quantify the impact of robot attributes – categorized as physical, functional, and relational – on different classes of emotions. The findings reveal that customers of restaurants and hotels were most influenced by the physical and relational attributes of service robots, respectively … |
| Anahtar Kelimeler |
| hotel and restaurant industry | sentiment analysis | service robots | Twitter | Word |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 3 |
| Scopus | 4 |
| Google Scholar | 6 |