期刊
JOURNAL OF LOCATION BASED SERVICES
卷 12, 期 2, 页码 94-118出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/17489725.2018.1493548
关键词
Similarity; tourist attraction; user-generated content; topic model; tripadvisor
资金
- Building Research Association of New Zealand through the National Science Challenge Building Better Homes, Towns and Cities: Ko nga wa kainga hei papakainga (BBHTC)
The motivation for tourists to visit a city is often driven by the uniqueness of the attractions accessible within the region. The draw to these locations varies by visitor as some travellers are interested in a single specific attraction while others prefer thematic travel. Tourists today have access to detailed experiences of other visitors to these locations in the form of user-contributed text reviews, opinions, photographs, and videos, all contributed through online tourism platforms. The data available through these platforms offer a unique opportunity to examine the similarities and difference between these attractions, their cities, and the visitors that contribute the reviews. In this work, we take a data-driven approach to assessing similarity through textual analysis of user-contributed reviews, uncovering nuanced differences and similarities in the ways that reviewers write about attractions and cities.
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