Where did you take those photos? Tourists’ preference clustering based on facial and background recognition

Abstract

The Internet and social media have become major channels for communicating destination image. Pictorial destination image, as shaped by user-generated photos posted on social media, is a key factor in potential tourists' perceptions and decision making. Over 50% of photos contain tourists' facial information. This paper proposes a novel approach to analyzing tourists' travel patterns and their preferences based on facial and photo content recognition techniques. Photos containing tourists' faces were filtered, and different tourist groups were classified by age and gender. Findings indicate that the grouped tourists expressed varying preferences in terms of photographed points of interest and backgrounds. These phenomena were explained based on the notion of tourists’ gaze and several psychological theories. • Proposed a novel destination image comparison method based on facial information. • Uses a total of 8704 photos to study the TDI differences among tourists toward Beijing. • A machine learning based sentiment and object recognition to analyze tourism photos. • Proved that tourists of varying profiles chose different backgrounds for their photos.