Text mining in tourism and hospitality research: a bibliometric perspective

Purpose The purpose of this study is to assess the current level of knowledge on the application of text mining in tourism and hospitality (T&H) research and provide a novel comprehensive framework for the field. This study also identifies gaps and proposes future research directions. Design/methodology/approach This bibliometric study analyzes 814 journal articles, sourced from Scopus between 2004 and 2024, and uses performance analysis and science mapping using Biblioshiny and VOSviewer software. Findings Over 50% of the articles were published between 2022 and 2024, reflecting a surge in text-mining applications in T&H research. These studies primarily focus on topics such as customer satisfaction, sustainability, destination image and COVID-19 effects, with sentiment analysis and topic modeling being the predominant techniques. The primary data sources are online reviews and microblogs. The review also highlights recent research trends (e.g. long–short-term memory, support vector machines and crisis) and classifies them into four conceptual categories concerning the application of text mining in T&H research: How? Where? Why? When? Originality/value This study comprehensively explores the evolution of T&H, contributions from research constituents and the intellectual structure of the field, providing a novel comprehensive framework while also assessing the field and highlighting its challenges.