探路者
接见者模式
主题(计算)
主题公园
多维标度
度量(数据仓库)
相似性(几何)
计算机科学
数据科学
广告
营销
万维网
数据挖掘
地理
人工智能
业务
旅游
图像(数学)
机器学习
程序设计语言
考古
作者
Qun Ren,Feifei Xu,Xiaowei Ji
摘要
Abstract We use pathfinder network scaling (PENETS) approach to measure and evaluate theme park visitors' online reviews. PFNETS as an effective tool of big data analytics can be used to identify unobserved meaningful interrelationships between concepts. Although there are many research analyzing online reviews, this study is the first attempt to use an analytical approach of PFNETS to explore online reviews in theme park visitor experiences. The article collects 14,142 effective reviews of the world's first Disneyland in California from TripAdvisor. Using parallel and similarity comparison in pathfinder scaling, four individually but fully connected networks were generated to reveal different visitors' experiences in different segments. The findings indicate the dissimilarity of concept relatedness between different segments and revealed the knowledge gap of marketing to different segments in theme parks.
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