Defining Interdisciplinarity through Topic Modelling Technique: An AI-Driven Approach

nterdisciplinary studies or research is a method of integrating knowledge and perspective from multiple disciplines to address complex problems. Interdisciplinarity consists of collaboration and cooperation from different fields to assemble together diverse perspectives and approaches in order to find innovative solutions. In this paper, we have measured interdisciplinarity using topic modelling approach. Topic modelling is an unsupervised natural language processing (NLP) technique for creating structured data from a collection of unstructured textual corpus without predefined training data. This text mining method have discovered hidden semantic patterns demonstrated by a text corpus to produce cluster of words, called “topics”. In this article, we have collected data from The Lens database (www.lens.org) and then applied topic modeling approach using the tool Coconut Libtool (www.coconut-libtool.com/). The final output is shown by network graphs, sunburst visualization, chord diagram etc. The main objective of the paper is to define the perspective of interdisciplinarity through topic model techniques.