基于机器学习的旅游目的地图像革命趋势研究

IF 4.5 3区管理学 Q1 BUSINESS

Journal of Vacation Marketing Pub Date : 2023-11-09 DOI:10.1177/13567667231213152

Xia Dong, Jianfeng Ma, Xiaoyu Zhang, Ahmed Shaalan, Qinyuan Chen, Shengyi Jia

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引用次数: 0

摘要

在旅游目的地形象研究中，主题建模、关键词之间的相互关系、形象演变趋势等方面受到的关注较少。本研究填补了现有文献的空白，在游客凝视理论的基础上，首次运用潜狄利克雷分配、文本可视化、话题演变趋势等方法对敦煌莫高窟的形象进行了研究。通过对旅游社交网络上22371条评价的分析，我们发现:(1)敦煌莫高窟形象的五个维度为突出性、独特性、丰富的文化性、便利性和巨大的影响力;(2)各维度关键词呈现出不同的协同关系;(3)维度演化趋势在方向和程度上存在差异。我们的研究丰富了已有的文献，对目的地营销领域具有重要的现实意义。

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Revolution trend investigation of tourism destination image with machine learning

In tourism destination image research, topic modeling, mutual relationships among keywords, and image evolution trends have received limited attention. Filling these gaps in the extant literature, based on tourist gaze theory, this study is the first to use Latent Dirichlet Allocation, text visualization, and topic evolution trend methods to explore the Dunhuang Mogao Grottoes’ image. Analyzing 22,371 reviews posted on tourism social networks, we find that (1) prominence, uniqueness, a rich culture, convenience, and enormous influence are five dimensions of the Dunhuang Mogao Grottoes’ image; (2) these dimension keywords display different cooccurrence relationships; and (3) the dimension evolution trends vary in direction and degree. Our study enriches existing literature and provides important practical implications for the destination marketing field.

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来源期刊

Journal of Vacation Marketing Multiple-

CiteScore

9.70

自引率

15.70%

发文量

期刊介绍： Journal of Vacation Marketing is a fully peer reviewed international journal that publishes original research and review articles on topics relating to the marketing of destinations and businesses/organisations involved in the wider tourism, hospitality and events industries. Its objective is to provide a forum for the publication of refereed academic papers and reviewed practitioner papers which are of direct relevance to industry, while meeting the highest standards of intellectual rigour.