Sentiment Analysis of Berlin Tourists’ Food Quality Perception Through Artificial Intelligence

Omid Shafiezad and Hamid Mostofi ()
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Omid Shafiezad: Hochschule für Technik und Wirtschaft (HTW) Berlin, Treskowallee 8, 10318 Berlin, Germany
Hamid Mostofi: Department of Work, Technology and Participation, Technische Universität Berlin, 10587 Berlin, Germany

Tourism and Hospitality, 2024, vol. 5, issue 4, 1-22

Abstract: This study examines how tourists perceive food quality in Berlin using AI-driven sentiment analysis tools. The goal is to understand the factors shaping tourists’ perceptions and provide insights to improve the hospitality industry and customer satisfaction. By analyzing reviews from online platforms, this research identifies key themes and trends in tourists’ feedback. The use of AI, specifically for sentiment analysis, supports efficient and detailed evaluation of customer opinions. This study employed lexicon-based sentiment analysis to evaluate tourists’ feedback on online platforms and compared the sentiment scores of textual feedback with their direct rating scores. The results show that integrating sentiment scores derived from AI tools with tourists’ rating scores provides deeper insights into service quality within the tourism sector.

Keywords: sentiment analysis; tourism research; artificial intelligence; visitor feedback analysis; culinary perception (search for similar items in EconPapers)
JEL-codes: Z3 Z30 Z31 Z32 Z33 Z38 (search for similar items in EconPapers)
Date: 2024
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