Sentiment Analysis to Measure Quality and Build Sustainability in Tourism Destinations

Fernando Borrajo-Millán, María-del-Mar Alonso-Almeida, María Escat-Cortes and Liu Yi
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Fernando Borrajo-Millán: Business Organization Department, Faculty of Economics and Business Administration, Autonomous University of Madrid, 28049 Madrid, Spain
María-del-Mar Alonso-Almeida: Business Organization Department, Faculty of Economics and Business Administration, Autonomous University of Madrid, 28049 Madrid, Spain
María Escat-Cortes: Business Organization Department, Faculty of Economics and Business Administration, Autonomous University of Madrid, 28049 Madrid, Spain
Liu Yi: School of Tourism Management, Sun Yat-sen University, Guangzhou 510275, China

Sustainability, 2021, vol. 13, issue 11, 1-14

Abstract: The models used for analyzing and measuring quality in tourist destinations are changing with the incorporation of new techniques derived from data science and artificial intelligence. Recent studies show how social media and e-word of mouth (e-WoM) are playing key roles in the perception and image diffusion of tourist destinations. Thus, it is necessary to look for new methods for analyzing the tourist management and attractiveness of tourist spots. This includes conducting a sentiment analysis of tourists that modifies former research methods based on previously proposed model, supported by a survey, which obtained predefined and incomplete results. This study analyzed the quality of tourism in Spain, a major tourist destination that is considered to be the country with the greatest tourist competitiveness according to the World Economic Forum, and in China, the country with the greatest level of development and potential. A sentiment analysis was carried out to measure the quality of tourist destinations in Spain, and this involved three challenges: (1) the analysis of the sentiments of Chinese tourists obtained from e-WoM; (2) the use of new models to measure the quality of a destination based on information from Chinese social networks, and (3) the use of the latest artificial intelligence analytical technologies. Our findings demonstrate how sentiment analysis can be a determining factor in measuring WoM and identifying areas of development in tourist destinations in order to build a more sustainable destination. The results includes the following aspects: (1) the use of real images with more empirical evidence, (2) the use of impressive and disappointing sentiments, (3) a “no comment status”, (4) elimination of stereotypes, and (5) the identification of new opportunities and segments.

Keywords: tourist attractions; tourist experiences; quality of tourist destination; sentiment analysis; WoM; e-WoM; social media; tourism management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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