Evolution of the computational science community: The dynamics of topics and collaborations in 24 years of ICCS and JoCS publications

We analyze the topic structure of 10,299 publications from the International Conference on Computational Science (ICCS) between 2001 and 2024 as well as the Journal of Computational Science (JoCS) between 2010 and 2023, using natural language processing techniques and network analysis. The computational science classification corpus was created into 15 main disciplines and 256 sub-disciplines sourced from Wikipedia. Among the 15 main disciplines, machine learning became the most popular topic after 2019, surpassing parallel & distributed computing, which peaked in the early 2010s. ICCS and JoCS show differences in research popularity in both first and second-level disciplines. Algorithm theory, Mathematical modeling, and network science are the most dominant topics in both ICCS and JoCS. Different disciplines present different trends in ICCS and JoCS. In the past 24 years, machine learning related topics have gained the most attention in both ICCS and JoCS. We also examined and compared the correlation between the trends in ICCS and Google search Trends. The collaboration of disciplinary networks of second-level disciplines exhibits a scale-free characteristic, and the network structures have undergone significant evolution over 24 years. Moreover, different disciplinary communities exhibit different ”introverted” and ”extroverted” community characteristics within the network. Additionally, we examined the life span of thematic workshops and the evolution of authors’ collaborations inside and after ICCS.