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

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.

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Publication Details

Journal
Tourism and Hospitality
Published
2024-12-10
DOI
https://doi.org/10.3390/tourhosp5040078
Citations
4
Primary Topic
Culinary Culture and Tourism
Type
article
Field-Weighted Citation Impact
1.39

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article

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

Hamid Mostofi, Omid Shafiezad
4 citations
Tourism and Hospitality
Culinary Culture and Tourism
1.39
article

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

Hamid Mostofi, Omid Shafiezad
article en
4 citations

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.

Tourism and HospitalityVol. 5(4)
HTW Berlin - University of Applied Sciences (DE), Technische Universität Berlin (DE)
Technische Universität Berlin
Decent work and economic growth
Openalex Percentile: Top 18%
Culinary Culture and Tourism
1.39
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Sentiment Analysis of Berlin Tourists’ Food Quality Perception Through Artificial Intelligence — Hamid Mostofi, Omid Shafiezad · Tourism and Hospitality (2024) | TGRS Research Map | TGRS