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Motivation and satisfaction of Chinese and U.S. tourists in restaurants: A cross-cultural text mining of online reviews

机译:中美游客在饭店的动机和满意度:在线评论的跨文化文本挖掘

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摘要

Tourists with dissimilar cultural backgrounds think and behave differently. Precisely capturing and correctly understanding the cultural difference will help tourism managers generate greater customer satisfaction and increased business revenue. To this end, this paper uncovers and compares the motivation and satisfaction of restaurant tourist customers coming from China and U.S. by investigating their online ratings and reviews. From two major online review communities, customer ratings and reviews have been retrieved, quantified, text-mined, compared, and interpreted using statistics, latent Dirichlet allocation, and frequency analysis. Results suggest that Chinese tourists are less inclined to assign lower ratings to restaurants, and are more strongly fascinated by the food offered, whereas U.S. tourists are more apt to be fun-seeking, and are less uncomfortable with crowdedness.
机译:具有不同文化背景的游客的想法和行为有所不同。准确地捕捉并正确理解文化差异将有助于旅游管理人员提高客户满意度并增加业务收入。为此,本文通过调查他们的在线评分和评论,发现并比较了来自中国和美国的饭店游客的动机和满意度。从两个主要的在线评论社区中,已使用统计数据,潜在的狄利克雷分配和频率分析来检索,量化,文本挖掘,比较和解释客户评级和评论。结果表明,中国游客不太愿意为餐馆分配较低的评分,并且更着迷于所提供的食物,而美国游客则更倾向于寻求乐趣,而在拥挤方面则不那么舒服。

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