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Leveraging AI-Driven Text Mining of Online Reviews to Uncover Culinary Experience Dimensions for International Tourists
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Author(s): Sidharth Srivastava (Galgotias University, India), Rajiv Mishra (Galgotias University, India), Vikas Singh (Galgotias University, India)and Amrik Singh (Lovely Professional University, India)
Copyright: 2025
Pages: 16
Source title:
Tracking Tourism Patterns and Improving Travel Experiences With Innovative Technologies
Source Author(s)/Editor(s): Ahmad Albattat (Management and Science University, Malaysia), Norhidayah Azman (Management and Science University, Malaysia), Marco Valeri (Niccolò Cusano University, Italy)and Amrik Singh (Lovely Professional University, India)
DOI: 10.4018/979-8-3693-9636-0.ch002
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Abstract
Culinary tourism draws numerous international tourists eager to savour local delicacies. With the widespread availability of Internet services, tourists often form their impressions of destinations by accessing digital reviews. This study aims to identify the dimensions of culinary experiences by analysing online reviews written by international tourists following their encounters with local cuisine. Data was gathered from TripAdvisor.com, a well-known website that reviews the travel and tourism sector. Eight hundred sixty-seven reviews from international tourists about Delhi Street food were gathered and subjected to qualitative analysis using Bigram analysis in R software to identify frequent phrases. These frequent phrases were then classified into distinct dimensions. The findings suggest that the identified dimensions of tourists' experiences with Delhi Street food can enhance the destination's image for international tourists evaluating online reviews. Future research could expand on these findings by utilizing larger sample sizes across different geographical locations.
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