Kristofer Söderström

Doctoral Student

Research areas and keywords

UKÄ subject classification

  • Information Studies


  • Sociology of science, Scientometrics, Innovation systems, Machine Learning


My Ph.D. project analyses contemporary Big Science facilities and its users, and how they affect the patterns of collaboration and productivity in the natural sciences. It aims to assess the premise that big machines are generic resources significant enough to give rise to new patterns of collaboration; that they promote interdisciplinary and inter-institutional research efforts; and that they positively impact scientific output and quality. It contributes to the current literature with a quantitative approach using statistical analysis and methods from machine learning on bibliometric data and user data.