Tourism flow is one of the main focuses of tourism research. The application of big data technology to tourism flow research is gradually becoming a trend. This study aims to understand the state-of-the-art tourism flow research from the perspective of big data application. We selected articles published in international academic journals as the research objects, summarized the research progress in relevant fields, and proposed research prospects. The analysis indicates that (1) since 2013, research on tourism flow, from the perspective of big data application, has shown a rapid development trend. Relevant research involves tourism, management, economy, information technology, and other fields with a development trend of diversified achievements. (2) based on keyword co-occurrence network analysis, it was divided into five condensed subsets. In terms of research themes, we found that achievements mainly focused on the measurement and characterization of tourism flow, the spatiotemporal pattern and effects of tourism flow, influencing factors, and prediction of tourism flow. In terms of application data, user-generated equipment and management data were the main data sources for analysis. The main methods included spatial statistics and analysis, network analysis, model construction, and interactive integration of different research methods. (3) existing research results show an imbalance in terms of themes, data, and methods. In the future, it is urgent to continue to explore and deepen the expansion of research themes, the fusion of big and small data, and the integration of multidisciplinary methods.