Júlia Koltai's proposal received the grant Lendület (“Momentum”) excellence programme of the Hungarian Academy of Sciences (MTA). Participating researchers include Ákos Huszár, Bence Ságvári and Attila Gulyás.

The abstract of the proposal:

Since the digital revolution, people's lives have increasingly moved to the online space. The digitalization of society has opened new areas and also new challenges for social science research. Digital space both reflects the social inequalities that exist in offline space and creates new cleavages between social groups. However, even those theoretical models that sociologists have developed in great depth and detail in recent decades on the stratification of society, which include dimensions from the digital world, are mostly based on survey data. Nevertheless, self-reported survey can only capture these digital inequalities to a limited extent, as it is more capable of measuring attitudes than behaviour. For the measurement of such digital differences, observation of people’s digital behaviour can be a more suitable method. At the same time, digitalization also results in new types of data on our offline life. Everyday activities are recorded on a computer every second, such as the location, time, or length of our phone calls, or our credit card spending. Data from the observation of digital behaviour and data generated by digitalisation can help us extend or refine our knowledge about how society is structured and works. The goal of this research would be to (1) create models which could predict social class purely from digital footprints of people by focusing on the digital behavioural differences of social groups defined by classical social structure theories, (2) detect new dimensions of social structure in the online space, with which existing theories could be extended or even new social stratification theories could be set, and (3) use digital, observational data to extend our knowledge about inequalities between different strata of the society.