Arbeitsbereich

Migration und Mobilität

Auf einen Blick Projekte Publikationen Team

Projekt

Das Verknüpfen sozialer Schichtung und geografischer Mobilität durch georeferenzierte Daten

Egor Kotov, Daniela Perrotta, Emilio Zagheni; in Zusammenarbeit mit John Palmer, Jonathan Kent (beide: Pompeu Fabra University, Barcelona, Spanien), Frederic Bartumeus (The Spanish National Research Council, Blanes Centre for Advanced Studies, Spanien), Jorge Cimentada (MPIDR)

Ausführliche Beschreibung

Recent advances in the analysis of digital trace data and in computational social science have enabled researchers to investigate questions at the intersection of geography, sociology, demography, and computer science. In particular, the collection of passive geo-located data has opened new opportunities for researchers to investigate old and new theories related to mobility, migration, and integration. Due to the difficulty of collecting geo-located data, classic research on social stratification has only been able to concentrate on using survey data, somewhat neglecting the nuanced role of spatial mobility and its effects on social mobility. The research literature shows, however, that social mobility is connected with the place of birth (i.e., a country or city) and that people are affected by the mobility of families over space and time.

We mainly seek to understand the way in which different sociodemographic and economic groups vary in their patterns of geographic mobility and look at the consequences in terms of exposure to other population groups, pollution, and green and cultural spaces. To this end, we utilize high-resolution spatiotemporal mobility data enriched with socioeconomic characteristics. Specifically, we will leverage a unique dataset from call detail records consisting of the everyday and hourly mobility patterns of groups of mobile phone users by age, sex, and income at a microgeographic scale, with the smallest unit being a census district. As such, this dataset allows frequent granular snapshots of mobility patterns to be made at an unprecedented scale in social mobility research. The dataset is focused on Spain, but it also covers mobility patterns spilling over to Portugal and France.

The Spanish data are released in aggregate form. Therefore, group-level mobility patterns identified by using these call-detail records data and implications of these patterns for inequality cannot be generalized to the level of individuals straightforwardly. To avoid this ecological fallacy, these group-level results can be verified at the individual level by using the Space Mapper smartphone application (which is part of the Activity-Space Project). Space Mapper is a privacy-focused open-source alternative to Google Location History; it allows users to track their daily mobility and view it on a map. Users of Space Mapper can also opt in to share their anonymized location history with researchers for scientific purposes. Researchers can also use Space Mapper to survey the users and to link the voluntarily shared mobility patterns with survey responses to retest inequality hypotheses at the individual level. Recruitment of participants for this study, which requires a mobile phone application, is envisaged to be made via targeted advertisement in online platforms.

Combining big passive geo-located mobility data with socioeconomic characteristics at the group level and analyses with individual-level traces and survey responses will enable us to understand social mobility and inequalities from a new and more robust perspective.