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

MakaleAçık ErişimScopus SJRQ2

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, 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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dc.contributor.authorAcar, Ayşegül
dc.contributor.authorTürten, Burak
dc.contributor.authorDiker, Ersin
dc.date.accessioned2026-10-22T10:21:45.227108417Z
dc.date.available2026-10-22T10:21:45.227108417Z
dc.date.issued2026
dc.description.abstractService 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.
dc.identifier.doi10.1080/1528008x.2024.2386590
dc.identifier.eissn1528-0098
dc.identifier.endpage1019
dc.identifier.issn1528-008X
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85201003812
dc.identifier.startpage994
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/13765
dc.identifier.volume27
dc.identifier.wosWOS:001287715500001
dc.language.isoen
dc.publisherRoutledge
dc.relation.ispartofJournal of Quality Assurance in Hospitality and Tourism
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjecthotel and restaurant industry
dc.subjectsentiment analysis
dc.subjectservice robots
dc.subjectTwitter
dc.subjectWord
dc.subject.classificationHospitality, Leisure, Sport & Tourism
dc.subject.classificationSocial Sciences - Other Topics
dc.subject.otherEXPERIENCE
dc.subject.otherBEAUTIFUL
dc.subject.otherHELPFUL
dc.titleAspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industry
dc.typeArticle
rdl.citation.openalex5
rdl.citation.scopus5
rdl.citation.wos4
rdl.oa.statusgreen
rdl.oa.statusclosed
rdl.oa.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85201003812&doi=10.1080%2f1528008X.2024.2386590&partnerID=40&md5=1be136d9730acfc471716d9c368227e5},
rdl.scopus.quartileQ2
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexEmerging Sources Citation Index (ESCI)