Natural language processing applied to tourism research: A systematic review and future research directions

Abstract

The social networks and the rapid development of new technologies have led to considerable changes in the tourism industry. Artificial intelligence, in particular natural language processing (NLP), presupposes a significant advantage in obtaining information on the mass content generated by online users concerning tourism services and products. This work presents a systematic review of the use of NLP in the tourism industry and research. We used the well-known PRISMA methodology, and 227 relevant studies over the last decade have been reviewed. Our analysis identified the main methodologies, tools, data sources, and other relevant features in the field. One of the principal contributions of this study is a taxonomy for using NLP in tourism. In addition, metadata were examined using a threefold approach: (i) general statistics, (ii) abstract text analysis, and (iii) keyword networks. Automatic analyses have identified six major topics in applying NLP to tourism issues and have shown that China, the United States, Thailand, and Spain share similar tourism issues or approaches.

Keywords

• Tourism
• Natural language processing
• Systematic review