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  • 标题:Sentiment Analysis to Measure Quality and Build Sustainability in Tourism Destinations
  • 本地全文:下载
  • 作者:Fernando Borrajo-Millán ; María-del-Mar Alonso-Almeida ; María Escat-Cortes
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2021
  • 卷号:13
  • 期号:11
  • 页码:6015
  • DOI:10.3390/su13116015
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要: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.
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