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.
Highlights
Many studies conducted in the last 40 years have examined the quality of tourist destinations at the level of tourist spots by using different theoretical models [1,2]
Following the incorporation of social networks and the extension of tourism contracting by platforms and other e-commerce systems, aspects of brand quality, word of mouth (WoM), and e-word of mouth (e-WoM) are extended [26,27,28,29,30]. This is demonstrated by the effects of social media, through the usage at the cognitive level and how affective images [31], brand quality, and customer value determine WoM and e-WoM [32], promoting tourist engagement and sharing intentions to visit the destination in the interactive eReferral platform, which results in eReferral sharing behavior
The new techniques are added to statistics, such as the support vector machine (SVM), naive Bayesian (NB), dynamic language model classifier, and lexicon matching methods, or a combination of models is used (SVM with others)
Summary
Many studies conducted in the last 40 years have examined the quality of tourist destinations at the level of tourist spots by using different theoretical models [1,2]. The use of new technologies for the treatment of enormous amounts of data collected on social networks and in e-commerce has led to the development of new analytical models of tourists’ quality perceptions. In this sense, analytical techniques and the establishment of results have been modified. Large amounts of data are analyzed in unstructured or text format or in a language that is difficult to treat in text mode; namely, Chinese The use of these techniques modifies the research system, which is not based on a previous model but is achieved by real contributions from social media users.
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