Analyzing TripAdvisor reviews of wine tours: an approach based on text mining and sentiment analysis

Elena Barbierato, I. Bernetti, Irene Capecchi
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引用次数: 12

Abstract

Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness.,The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020.,The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction.,The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires.,The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas.,The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas.,The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.
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分析TripAdvisor对葡萄酒之旅的评论:一种基于文本挖掘和情感分析的方法
葡萄酒打包旅游作为葡萄酒旅游的一个特定方面,迄今为止在研究中一直被忽视,因此,本研究的目的是研究托斯卡纳(意大利)葡萄酒旅游成功的关键因素,评估其优势和劣势。该研究结合了文本挖掘、情感分析和自然语言处理等方法,利用猫途鹰平台的数据,通过自动程序从2010年至2020年的600次旅行中获得了9616条评论。作者总结了研究对象所表达的成功葡萄酒之旅的六个要素:导游;后勤方面;酒的质量;食物的质量;配套的旅游和娱乐活动;风景和历史村落。与成功相关的关键力量是将领先的葡萄酒产品与食物,景观和历史村庄相结合,而主要的批评是关于旅游的组织和规划。此外,导游在消费者满意度中也起着根本性的作用。该方法的局限性与所用数据的来源有关。主要原因是,TripAdvisor不允许你获得写评论的游客的社交和个人信息;因此,这些方法对传统的问卷调查有很大的补充作用。所提出的模型既可以被专业人员用来提高产品质量,也可以被政策制定者用来促进优质葡萄酒产区的地域发展。该模型可为政策制定者促进优质葡萄酒产区的地域发展提供参考。我们测试的方法很容易转移到许多国家和作者的知识,第一次尝试结合多维尺度,情感分析和自然语言处理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.90
自引率
11.10%
发文量
23
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