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Tourism is one of the most competitive, lucrative, and socially important economic segments in the world. Therefore, understanding the behavior of tourists is strategic for improving services and results. Many studies in the literature explore this issue using traditional data, such as surveys. These approaches provide reliable, precise information, but it is hard to obtain on a large scale, making studying worldwide patterns difficult. Location-Based Social Networks (LBSNs) could minimize these problems due to the ease of acquiring large amounts of detailed behavioral data. Nevertheless, before using such data, it is imperative to determine whether the information reveals behaviors comparable to traditional data - our ground truth. Thus, this work investigates whether the international flow of tourists measured with LBSN data is similar to the behavior estimated by the World Tourism Organization with traditional data sources. Our results suggest that LBSNs data represent the studied behavior well, indicating that they could be used in research regarding tourism mobility at different levels.