Computational Social Science

Computational social science (CSS) applies computational methods to understand social phenomena, aiming to extract insights from large-scale datasets and improve the reliability and efficiency of social science research. Current research heavily utilizes large language models (LLMs) and other machine learning techniques for tasks like text analysis, opinion prediction, and bias detection, focusing on improving data quality, mitigating biases inherent in models and datasets, and developing robust methodologies for handling imperfect data. The field's significance lies in its potential to enhance the rigor and scalability of social science research, leading to more accurate and nuanced understandings of complex social issues and informing evidence-based policymaking.