New Methodological Approaches for Migration and Mobility Studies: From Traditional to Big Data

Research on human migration and mobility has been undergoing an unprecedented transformation; big data and artificial intelligence techniques (i.e., machine learning, deep learning, natural language processing, etc.) have been increasingly adopted to better understand why and how people move, the drivers and consequences of human movements, as well as migrants’ social integration processes in their settled locations. While these relatively new data sources and methodologies have proven to be useful in some contexts, they are far from being generalizable. In particular, many theoretical and empirical challenges remain to be addressed, such as the representativeness of digital traces, biases within data and algorithms, and the explainability and interpretability of algorithms. Other obstacles encompass data accessibility and protection, as well as privacy and ethical concerns.

Against the background above, this special issue seeks to: i) showcase new data sources (both quantitative and qualitative) and demonstrate their usability for migration research; ii) investigate how new data sources may complement or substitute traditional research materials; iii) develop methodological approaches for processing, analyzing, and combining different types of data; and iv) explore solutions for optimizing the use of big data and AI systems for studying migration and mobility while ensuring privacy and protection of individuals.

We welcome empirical or conceptual contributions on the use (or combination) of different types of data materials and computational models to study migration phenomena. Potential topics are including but not limited to:

- understanding and estimating migration flows and stocks;
- the policy – migration nexus;
- attitudes towards migration and migrants (e.g. using sentiment analysis, discourse type and media portraying of migrants, polarisation of the discourse with respect to human migration, etc.);
- ethics of big data and AI in the context of human migration;
- impact of such digital technologies upon migration, migrants and migration studies;
- migrants’ integration processes and life trajectories;
- case studies utilising non-traditional data sources and techniques;
- predicting/projecting future migration and its consequences;
- biometrics, AI supported decision making for border management;
- blockchain technologies and digital identities;
- migrants’ health and wellbeing.

Keywords: human migration, big data, artificial intelligence, machine learning, deep learning, natural language processing, social integration

Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.