This project focuses on developing and evaluating machine learning algorithms for processing online social network data. Specifically, Björn’s research explores how information, ideas, and behaviours spread (social contagion) within these networks.
By harnessing advances in machine learning, particularly in natural language processing and graph-based learning, Björn aims to create methods that analyse the vast streams of data from online social networks and uncover new, nuanced insights.
Additionally, since most online platforms use machine learning algorithms to shape the content we see and the connections we form, a major goal of his work is to assess how these algorithms influence social contagion.
