Comparing Global Tourism Flows Measured by Official Census and Social Sensing
Lucas Skora, Helen Senefonte, Myriam Delgado, Ricardo L\"uders, Thiago, Silva

TL;DR
This study compares traditional tourism data with location-based social network data across countries, finding that LBSN data can reliably reflect tourist behavior in most cases, enabling large-scale mobility studies.
Contribution
It evaluates the validity of using LBSN data as a proxy for traditional tourism data across countries, highlighting its potential for large-scale behavioral analysis.
Findings
LBSN data generally aligns with traditional data for most countries.
High correlation indicates LBSN data can be used for mobility research.
Exceptions exist where LBSN data does not reflect traditional measures accurately.
Abstract
A better understanding of the behavior of tourists is strategic for improving services in the competitive and important economic segment of global tourism. Critical studies in the literature often explore the issue using traditional data, such as questionnaires or interviews. Traditional approaches provide precious information; however, they impose challenges to obtaining large-scale data, making it hard to study worldwide patterns. Location-based social networks (LBSNs) can potentially mitigate such issues due to the relatively low cost of acquiring large amounts of behavioral data. Nevertheless, before using such data for studying tourists' behavior, it is necessary to verify whether the information adequately reveals the behavior measured with traditional data -- considered the ground truth. Thus, the present work investigates in which countries the global tourism network measured…
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Taxonomy
TopicsDiverse Aspects of Tourism Research · Human Mobility and Location-Based Analysis · Digital Marketing and Social Media
