The cross-border practices of people beyond migration and tourism are often overlooked. However, the increase of frequent social interactions and mobilities of people crossing country borders for work, shopping, services and leisure contribute to (re)shaping functional cross-border regions. We propose a conceptual framework using a big data approach to provide new insights from the individual-level cross-border mobility of people. We used Twitter data as a promising transnational data source to empirically examine who, when and where the borders are crossed in the case of Luxembourg – one of the busiest cross-border regions in Europe. Special attention has been given to cross-border commuters. We evaluated our findings to demonstrate the feasibility of the proposed approach as the proof-of-concept for cross-border research. We mapped prospects and challenges to improve the operationalization of the proposed approach relevant to cross-border research and shared our source code to encourage further method development. Finally, we have highlighted how this information from social media data can benefit research and practice for policy and planning in cross-border regions. ; Peer reviewed