Abstract

Nowadays, social networking sites (SNS) are used for posting and seeing beautiful photographs. Although many visitors click photographs in theme parks and post them on SNS, finding appropriate photo spots using SNS is not easy because of the enormous number of posted images. This study proposes recommendation algorithms that will help visitors find appropriate photo spots. As test case, we chose Tokyo Disneyland (TDL), which posts its photographs on Twitter. Twitter characteristically merges several photographs into a single image called a collage, which shows the excursion history of visitors. Based on these histories, we apply a collaborative filtering algorithm, which recommends photo spots to visitors. Before designing a photo spot recommendation system for theme parks, we must know the intentions and preferences of theme park visitors. To acquire this knowledge, we conducted a questionnaire survey. The results suggested that male subjects prefer scenic and pose-friendly photo spots, whereas female subjects tend to choose spots that render them “instagrammable,” “beautiful,” and “cute”. Based on these findings, we categorized photo spots inside TDL and created a prototype recommendation system.

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