Comparative clustering of destination attractions for different origin markets with network and spatial analyses of online reviews

Abstract

In this paper we address the problem of clustering tourist attractions according to the tourists' interests that these attractions serve. With growing diversity of tourist interests, there is a new understanding of tourist clustering as formed by multiple proximity metrics with the social distance of the tourists playing a role similar to geographical distance. The study clusters Florida's destination attractions according to the visitation patterns of tourists from different origin markets: Floridians, out-of-state US visitors, and international travelers. Online reviews of attractions served as the proxy data for actual visitations. The study employs network analysis, spatial analysis, and geo-visualizations to deal with the data in the most comprehensive way. The same three attractions-interests clusters (Entertainment, Heritage, and Nature) emerged for each origin market. The similarities and differences in cluster composition and in how these clusters utilize attractions in the state of Florida are analyzed and discussed.