Aspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industry

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, with functional attributes having the least impact. The logistic regression analysis offered significant insights into how service robot attributes influence consumer experiences in hotels and restaurants.

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Publication Details

Journal
Journal of Quality Assurance in Hospitality & Tourism
Published
2024-08-09
DOI
https://doi.org/10.1080/1528008x.2024.2386590
Citations
3
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
1.04
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article

Aspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industry

Burak Türten, Ersin Diker, Ayşegül Acar
3 citations
Journal of Quality Assurance in Hospitality & Tourism
AI in Service Interactions
1.04
article

Aspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industry

Burak Türten, Ersin Diker, Ayşegül Acar
article en
3 citations

Abstract

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, with functional attributes having the least impact. The logistic regression analysis offered significant insights into how service robot attributes influence consumer experiences in hotels and restaurants.

Journal of Quality Assurance in Hospitality & Tourism
Gümüşhane University (TR), Karabük University (TR)
Decent work and economic growth
Openalex Percentile: Top 20%
AI in Service Interactions
1.04
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