The effect of COVID-19 on cross-border mobilities of people and functional border regions: the Nordic case study from Twitter data

ABSTRACT Mobility is a global megatrend in our contemporary world as people are constantly crossing nation-state borders for migration, tourism, work and due to mobile transnational lives. Cross-border practices contribute to (re)produce functional border regions between different countries. The current amount of information on the geographies of cross-border mobilities of people, the creation of functional cross-border regions and how these regions change over time is inadequate. As transnational phenomena are fragile to global disruptions and prone to ‘rebordering’ in times of emergency, we lack knowledge of how the COVID-19 crisis affected border practices and functioning regions. We consider mobility to be a tool for understanding society and used big data to examine cross-border mobilities between the five Nordic countries: when and where borders were crossed, how mobilities captured functional border regions, and evaluated the influence of COVID-19 on mobilities and functional border regions from a spatio-temporal perspective. The feasibility of the proposed methodology for monitoring cross-border mobilities and border regions to improve planning and development of border regions and decision-making in future crises is discussed. We studied a 4-year Twitter dataset, including the first year of the pandemic until February 2021. We found that overall cross-border mobility decreased by 68% due to the pandemic, yet with geographical and temporal variations. We showed how the influence of the pandemic on the spatial extent of functional border regions varies for a range of reasons for cross-border mobility. We discuss the feasibility of the proposed approach for monitoring cross-border interactions as the proof-of-concept for capturing functional border regions to improve planning and development of border regions and decision-making in future crises. Finally, we highlight future avenues in enhancing our proposed methodology to improve information on cross-border mobilities derived from social media data such as Twitter.