Using heterogenous information networks for integrative discourse mapping

This short paper presents a novel way of mapping knowledge communities in discourse by utilizing heterogenous information networks (HINs) and a two-stage grouping procedure. After laying out the theoretical foundations of a discourse analytical framework grounded in the sociology of knowledge, it will demonstrate the applicability of the framework on the platform Twitter. In exploratively analysing a sample of 6.317.324 tweets on the Covid19 pandemic, we will show how clustered HINs can make visible the social embeddedness of knowledge production in digital environments.