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A machine learning approach to cluster destination image on Instagram
Tourism Management ( IF 10.9 ) Pub Date : 2021-03-18 , DOI: 10.1016/j.tourman.2021.104318
Veronika Arefieva , Roman Egger , Joanne Yu

Symbols are powerful in branding and marketing to represent tourist attractions. By bridging semiotics, marketing, and data science in the tourism context, this study uncovers the destination image based on Instagram photographs. This study constructed a novel methodological framework by evaluating different machine learning models to group textual information based on pictorial content. The results highlighted specific destination image clusters such as the wilderness and spirituality of alpine experiences. This information facilitates marketers' understanding of tourists’ preferences and movement. It also discloses blind spots that are less promoted by the marketers.



中文翻译:

一种在Instagram上聚类目标图像的机器学习方法

符号在品牌和营销中具有很强的代表性,可以代表旅游景点。通过将符号学,市场营销和数据科学结合到旅游环境中,本研究发现了基于Instagram照片的目的地图像。这项研究通过评估不同的机器学习模型以基于图片内容对文本信息进行分组,构建了一个新颖的方法框架。结果突出显示了特定的目的地图像群,例如高山体验的荒野和灵性。这些信息有助于营销人员了解游客的喜好和活动。它还公开了营销人员较少推广的盲点。

更新日期:2021-03-19
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