1. Design and analysis of social science studies
  2. Data science
    • Applied statistics and data analysis
    • Network analysis
    • Predictive modelling
    • Development of data-based tools and applications (R, Shiny)
  3. Computational Social Science
    • Mathematical modeling of social phenomena
    • Computational modelling (e.g. agent-based)


  1. Quantitative analysis of social structures and processes, e.g.:
    • Competition and collaboration in science
    • Quantitative empirical studies of law and judicial system.
    • Diffusion of innovation in social networks and society.
    • Social and psychological determinants and consequences of the use of information and communication technologies.
    • Structural determinants of communication and news consumption in online social networks. Behavioural profiling.
    • Organizational Network Analysis
  2. Social Network Analysis
  3. Deriving evidence-based and data-driven solutions.

Contact with Computational Social Science Lab: lp.ude.mcinull@iksrotab.d