Volume 27, Issue 4-1, December 2023
QUANTIFYING NATIONALITY BIAS IN SOCIAL MEDIA DATA ON DIFFERENT PLATFORMS FOR VISITOR MONITORING IN NIKKO NATIONAL PARK, JAPAN
Authors: Masahiro Kajikawa, Takafumi Miyasaka, Yutaka Kubota, Akihiro Oba, Katori Miyasaka
Abstract: Geotagged social media data have been used widely for visitor monitoring in protected areas. The data might, however, over or underestimate visitors from specific countries due to nationality bias, i.e., differences between nationality of actual visitors versus those visitors who post on social media. This study aimed to quantify nationality bias in social media data for visitor monitoring. We conducted a questionnaire survey in Nikko National Park, Japan. Questions covered the nationality of visitors and their usage of social media, and other visitor attributes and behavior. Foreign visitors had significantly different attributes and behaviors compared to Japanese. Non-Japanese Asian visitors were overrepresented in Instagram and Facebook data. In comparison, the X platform was more representative of all visitors. Nationality bias in different platforms needs more attention and further study in different areas.
Keywords: Country of origin, Nature-based tourism, Representativeness, Sampling bias, Social networking service, Spatial visitor distribution, Twitter
Article info:
Received: August 30, 2023 | Revised: November 22, 2023 | Accepted: November 27, 2023