A data-driven approach to exploring similarities of tourist attractions through online reviews. (3rd April 2018)

• Record Type: Journal Article
• Authors: McKenzie, Grant; Adams, Benjamin
• Is Part Of: Journal of location based services. Volume 12:Number 2(2018)
• Page Start: 94
• Page End: 118
• Publication Date: 2018-04-03
• Subjects: Similarity -- tourist attraction -- user-generated content -- topic model -- tripadvisor; Mobile computing -- Periodicals; Multimedia systems -- Periodicals; Local area networks (Computer networks) -- Periodicals; Wireless communication systems -- Periodicals; 004.68
• DOI: 10.1080/17489725.2018.1493548
• Languages: English
• ISSNs: 1748-9725

Abstract

ABSTRACT: 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.