Computational social science is the study of people, their behavior, and the relationships between people. The digital transformation of various industries under the AI technology trend has made new possibilities for research in social science: computational social scientists use new methods such as machine learning to collect and analyze data with unprecedented depth and breadth; network analysis and word vectors help us understand the reasons behind societal phenomena such as TikTok becoming a source of misinformation in the Israeli-Palestinian conflict, and pave the way for new paths in the study of social issues and culture. In a future marked by conflicts and challenges, the application of computational social science will become even more rich and extensive. How do we then understand this discipline from a rigorous definition?

FusionX Computational Social Science will start from the theoretical foundations, taking you deep into the understanding of classic machine learning algorithms such as support vector machines, as well as deep learning methods such as neural networks applied in projects like natural language processing and data mining; through practice using Python and a series of tools to replicate the models from classic papers in computational social science, systematically exercising the ability to choose models, adjust parameters, and analyze results in multidisciplinary research.