Seeing is visiting: discerning tourists' behavior from landmarks in ordinary photos

The unprecedented development of the internet has compelled a growing number of tourists to share their photographs on social media. These images convey valuable memories and points of interest. As photography and content sharing have become commonplace among visitors, pictorial digital footprints r...

Full description

Saved in:
Bibliographic Details
Published inCurrent issues in tourism Vol. 26; no. 15; pp. 2494 - 2512
Main Authors Ning, Deng, Yujie, Qu, XiaoBin, Cheng, Jing, Qin
Format Journal Article
LanguageEnglish
Published Abingdon Routledge 03.08.2023
Taylor & Francis Ltd
Subjects
Digital media
Feasibility studies
Footprints
Instagram
landmark recognition
Landmarks
Photography
Recognition
Social networks
Tourism
Tourist behavior analysis
Tourists
UGC photos
Online AccessGet full text

Cover

More Information
Summary:The unprecedented development of the internet has compelled a growing number of tourists to share their photographs on social media. These images convey valuable memories and points of interest. As photography and content sharing have become commonplace among visitors, pictorial digital footprints represent a prevalent topic in tourism research. Studies on tourists' movement trajectories hold great importance for destination management, marketing, and services. Flickr is a popular source in photo-based tourism research given the digital footprints embedded in photos' metadata; however, the site's bottlenecks (e.g. declining user activity, overly professional photographs) raise concerns. Scholars have instead gradually shifted their attention to emerging photo platforms such as Instagram-yet these pictures do not contain geographical information. Taking Beijing as a focal location, we introduce an approach in which landmark recognition complements the geographical cues in Instagram photos. Instagram check-in data and data identified through landmark recognition are validated. Ultimately, the recognized landmark information appears highly correlated with check-in data. This study demonstrates the feasibility of landmark recognition for extracting tourists' footprints from ordinary content in user-generated photos. Findings also confirm that many photos from general social media platforms can serve as alternative and representative data sources in photo-based tourism research.
ISSN:1368-3500
1747-7603
DOI:10.1080/13683500.2022.2089547