Exploring memorable gastronomic experiences: Automatic topic modelling of TripAdvisor reviews

IF 1.1 Q3 GEOGRAPHY
Marek Nowacki, Andrzej Stasiak, A. Niezgoda
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引用次数: 0

Abstract

The article aims to identify memorable gastronomic experiences reported online and verify their relationships with the type of cuisine served and restaurant location. This study used text mining, LDA, Pearson’s chi-squaredtest and sentiment analysis. All 48,378 English reviews posted by TripAdvisor users concerning 155 restaurants in Krakow were scraped. Eight features that characterise MGEs were identified (service/staff, atmosphere,cuisine/food (taste), drinks, local specialities, location/setting, price & value and table booking). There are statistically significant differences in the frequency of the topic experiences depending on the location of restaurants in the city.
探索难忘的美食体验TripAdvisor 评论的自动主题建模
文章旨在找出网上报道的令人难忘的美食经历,并验证它们与所提供菜肴的类型和餐厅位置之间的关系。本研究采用了文本挖掘、LDA、皮尔森卡方检验和情感分析等方法。我们收集了 TripAdvisor 用户发布的有关克拉科夫 155 家餐厅的全部 48,378 条英文评论。研究确定了八种 MGE 的特征(服务/员工、氛围、菜肴/食物(口味)、饮品、当地特色、地点/环境、价格和价值以及订座)。在统计意义上,不同地点的餐厅在主题体验的频率上存在明显差异。
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
Geographia Polonica
Geographia Polonica GEOGRAPHY-
CiteScore
2.40
自引率
0.00%
发文量
9
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