Topic modelling approaches to aggregated citation data

In this research in progress paper we report on preliminary results from the proposed novel uses of topic modelling approaches to bibliographic references as sources for “bags-of-words” instead of actual text content in scientometric settings. The actual cited references, viewed as concept symbols for paradigmatic approaches to earlier research, could thereby be used to cluster research. We will demonstrate an explorative approach to using cited reference topics for the discovery of hidden semantic reference structures in a set of scientific articles. If found fruitful and robust, this approach could complement existing text based and citation based techniques to clustering of research that might bridge the two approaches. By approaching references as “words” and reference lists as “sentences” (or documents) of such “words”, we demonstrate that the topical structure of document collections can also be analyzed using an alternative and complementary source of content, which additionally provides an interesting perspective on bibliographic references as units of a meta language describing document content.