The Geographic Spread and Preferences of Tourists Revealed by User-Generated Information on Jeju Island, South Korea

Abstract

Recreation and tourism are important ways that people interact with and derive benefits from natural environments. Understanding how and where nature provides recreational opportunities and benefits is necessary for management decisions that impact the environment. This study develops and tests an approach for mapping tourism patterns, and assessing people’s preferences for cultural and natural landscapes, using user-generated geographic content. The volume of geotagged images and tweets shared publicly on Flickr and Twitter and proprietary mobile phone traffic provided by a telecommunications company, are used to map visitation rates to potential tourist destinations across Jeju Island, South Korea. We find that densities of social media posts and mobile phone traffic are all correlated with ticket sales and counts of gate entries at tourist sites. Using multivariate linear regression, we measure the degree to which attributes of the natural and built environment explain variation in visitation rates, and find that tourists to Jeju Island prefer to recreate near beaches, sea cliffs, golf courses and hiking trails. We conclude that high-resolution and spatially-explicit visitation data provided by user-generated content open the door for statistical models that can quantify recreation demand. Managers and practitioners could combine these flexible and relatively inexpensive user-generated data with more traditional survey data to inform sustainable tourism development plans and policy decisions. These methods are especially useful in the context of landscape or regional-scale ecosystem service assessments, where there is a need to map the multiple ecological, economic, and cultural benefits of the environment.

Using mobile phone data to examine weather impacts on recreational ecosystem services in an urban protected area

“…Flickr and Instagram have been the dominant sources of these big data 7,[31][32][33][34][35][36][37][38] while some studies rely on GPS tracking devices, smartphone-based GPS devices, and infrared mechanical counters 7,39,40 . Moreover, there are studies applying mobile phone data to examine visitation to other nature-based recreation sites, such as urban parks [41][42][43] .…”

Next-generation visitation models using social media to estimate recreation on public lands

“…Data included all publicly available posts that were tagged to a location within the site boundary 8 , 11 , 17 . Flickr and Twitter users have the option to share the latitude and longitude where the content was created—using coordinates of the GPS unit in their phone or camera—or to assign a location manually 42 . Flickr images were retrieved from November 16–25, 2018 by querying the Flickr application programming interface (API).…”

Combining Social Media and Mobile Positioning Data in the Analysis of Tourist Flows: A Case Study from Szeged, Hungary

“…Understanding the spatial and temporal aspects of the travel behavior of tourists is essential to comprehending their travel activities [16]. For example, managers and practitioners seeking sustainable tourism development can especially make good use of such user-generated data in their work [11]. Social media data can support product development and destination management in tourism in many different ways [8,17].…”

“…By processing and analyzing real-time data, and developing and implementing appropriate answers, the tourism products of a destination can be flexibly adapted to the needs and desire of consumers [10]. Collecting and analyzing data from social media not only requires less financial resources than surveying visitors, but such data are also more accurate, and due to space-and time-stamps have less limitations in spatial and temporal analysis [11].…”