Predicting the evolution of physics research from a complex network perspective

• Main Authors: Liu, Wenyuan, Saganowsk, Stanislaw, Kazienko, Przemysław, Cheong, Siew Ann
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2022
• Subjects: Science::Physics; Knowledge Evolution; Machine Learning
• Online Access: https://hdl.handle.net/10356/155409
• Institution: Nanyang Technological University

The advancement of science, as outlined by Popper and Kuhn, is largely qualitative, but with bibliometric data, it is possible and desirable to develop a quantitative picture of scientific progress. Furthermore, it is also important to allocate finite resources to research topics that have the growt...