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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.

旅游与酒店管理研究中的文本挖掘:一种文献计量学视角

研究目的

本研究评估了文本挖掘在旅游与酒店管理(T&H)研究中的应用现状, 并提供了该领域的全新综合框架。同时, 研究还识别了当前存在的研究空白并提出了未来的研究方向。

研究方法

本研究通过文献计量分析方法, 对2004年至2024年间Scopus数据库中814篇期刊文章进行分析, 采用Biblioshiny和VOSviewer软件进行绩效分析和科学映射。

研究发现

超过50%的文章发表在2022年至2024年间, 反映了文本挖掘在T&H研究中的应用激增。这些研究主要集中在顾客满意度、可持续性、目的地形象以及COVID-19影响等主题, 情感分析和主题建模是主要使用的技术。主要数据来源为在线评论和微博。该综述还揭示了近期的研究趋势(如长短期记忆LSTM、支持向量机SVM、危机管理), 并将其归纳为四个文本挖掘在T&H研究中的概念类别:如何?在哪里?为什么?以及何时?

研究创新

本研究全面探索了T&H领域的演变、研究贡献者的作用以及该领域的知识结构, 提供了一个新的综合框架, 评估了该领域的发展并突出了其挑战。

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