Using Network Science To Gain Insights Into Scientific Literature

Using Network Science To Gain Insights Into Scientific Literature by Adeel Javed (2021)

At the beginning of 2020 a novel disease related to family of coronavirus broke out from Wuhan, China. It infected a large population and spreaded all over the world. The disease is declared as global pandemic by world health organization (WHO). Various researchers from different domains are working against the spread of virus according to their knowledge domains. Document clustering is widely studied prob- lem to cluster related objects for better organization and summarization of their contents. In this research we present a novel way of document clustering using the concepts of network science. We use community detection algorithms on projected single mode network of articles from a bipartite network of articles and keywords to find clusters of articles related to (COVID-19). The clustering and presentation of top most important keywords in a specific cluster help us to identify group of articles on a topic related to specific domain. Evaluation shows that our proposed approach performs better than traditional clustering techniques.