Transnational Transition to Adulthood: New insights from social media data

Social media data represent new data sources providing new opportunities (and challenges) for the
Social Sciences (Savage & Burrows 2007; McCormick et al. 2015). The project will investigate the
opportunities offered by Facebook as a potential data source for demographic research.
In particular, I propose an application for social media data which studies migration movements in
Europe by exploiting the digital traces that individuals leave as posts on Facebook (and potentially other
social media). As it is stated by Raymer et al. (2013), international migration data in Europe are
"inconsistent in availability, definition, and quality". European countries do collect separately migration
data with different systems and designs. I will produce estimates of the flows of people (by gender,
education etc.) migrating between European countries based on the change in the location that they
specify on Facebook. Such estimates will complement existing but inaccurate official estimates of
migration flows. The project will also have a theoretical contribution to the socio-demographic
literature, by documenting the emergence of a 'transitional transition to adulthood' and its drivers (work
or study-related reasons). I propose to utilise Bayesian inference which will allow estimation of the parameters of a complex
model with hierarchical structure. It will also provide measures of uncertainty for the parameters and
other quantities of interest. Bayesian analysis of statistical models will require applying and possibly
extending cutting-edge computational methods, and may also lead to development of new software in
languages such as R and Python, which will be transferrable to other applications.