Interests and substantive projects
I have used a variety of methodological approaches — ranging from natural language processing to network analysis — to study attention dynamics in parliaments, the digital development of nations, as well as gendered patterns of behaviour online. For my PhD dissertation, I extend and build on this existing work.
Currently, I am working on a project that aims at understanding how occupational gender segregation comes about. In this project, I am especially interested in the role individuals’ personal networks and local-level exposures play in the decision to change occupation and how exposure networks shape perceived opportunity structures. With the help of Swedish Register data I try to understand (1) the role that exposures to peers at school, the workplace and family members plays in choosing to change occupations (exposure effects) (2) the role endogenous dynamics play, i.e. the amount of occupational segregation that is due to codependent mobility behaviour between genders (endogenous dynamic), and (3) the role ‘boundaries’ in the mobility network play for transitions. I work on this project collaboratively with Károly Takács, Martin Arvidsson, and Maria Brandén.
I am trained in Social Network Analysis, Statistics, Natural Language Processing, Data Analytics at Scale (Big Data), and Machine Learning. I work mostly in Pyhton and R.