RESTORANLARDA ROBOT GARSONLARIN KULLANIMINA YÖNELIK TOPLUMSAL ALGILAR: SOSYAL MEDYADA DUYGU VE İÇERİK ANALİZİ

Abstract

Bu çalışmada restoranlarda robot garsonların kullanımına yönelik toplumsal görüşü çevrimiçi kullanıcı yorumları ile belirlenmesini amaçlamaktadır. Bu amaç kapsamında, restoranlarda kullanılan hizmet robotları ve robot garsonlarla ilgili en çok yorum alan ilk on beş YouTube videosundaki çevrim içi kullanıcı yorumları duygu analizi ve içerik analizi yöntemiyle incelenmiştir. Duygu analizinde, Lexicon (NLP) tabanlı bir yaklaşım kullanılarak yorumlar olumlu, nötr ve olumsuz olarak duygu kutupları belirlenmiştir. Duygu analizinin sonuçlarını desteklemek için ise içerik analizi yönteminde MAXQDA kullanılmıştır. Analiz sonuçlarına göre, kullanıcı yorumlarının %37,1’i olumlu, %32,5’i olumsuz ve %30,4’ü nötr olarak belirlenmiştir. Bu çalışma özellikle robot garsonların restoranlarda uygulanmasının henüz yeni olduğu göz önüne alındığında, çevrim içi yorumlar yeni hizmetlerin ve oluşumların anlaşılmasına katkı sağlaması bakımından önemlidir. Metodolojik olarak bu araştırma robot-insan etkileşiminde toplumun teknoloji kabulü ve görüşünün belirlenmesinde duygu analizi gibi yenilikçi bir yaklaşım sunmaktadır. Elde dilen bulguların ise, alan yazına teorik, sektörel uygulamalara ise pratik katkılar sunması açısından önemli görülmektedir.

Keywords

• Robot
• Restoran
• YouTube
• Kullanıcı yorumları
• Duygu analizi

SOCIAL PERCEPTIONS ON THE USE OF ROBOT WAITERS IN RESTAURANTS: SENTIMENT AND CONTENT ANALYSIS ON SOCIAL MEDIA

Abstract

In this study, it is aimed to determine the opinions of online user comments written on videos about robot waiters used in restaurants on the YouTube platform. For this purpose, online user comments on the top fifteen most commented YouTube videos about service robots and robot waiters used in restaurants were analyzed through sentiment analysis and content analysis. In sentiment analysis, a Lexicon (NLP)-based approach was used to polarize the comments into positive, neutral, and negative sentiments. To support the results of sentiment analysis, MAXQDA was used in the content analysis method. According to the results of the analysis, 37.1% of user comments were positive, 32.5% were negative, and 30.4% were neutral. This study is particularly important given that the implementation of robot waiters in restaurants is still in its infancy, as online reviews contribute to the understanding of new services and entities. Methodologically, this research offers an innovative approach, such as sentiment analysis, in determining society's acceptance and opinion of technology in robot-human interaction. The findings are considered important as they will provide theoretical contributions to the literature and practical contributions to sectoral applications.

Keywords

• Robot
• Restaurant
• YouTube
• User reviews
• Sentiment analysis

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