Computational Social Science
Overview
Computational social science studies how people and groups behave, interact, and organize, and how those processes shape outcomes such as opinion, inequality, and political change. Researchers combine statistical and causal analysis with social network analysis, natural language processing, and digital trace data from platforms, surveys, archives, and administrative records. Agent-based models and large language model agents are increasingly used to simulate social interaction, while text models help measure concepts such as ideology, sentiment, and trust. A central challenge is establishing that these measurements and simulations represent real social processes: models can match average patterns while missing human diversity, context, or causal mechanisms.
Latest papers
166 papers15 papers in the last four weeks, down 35% on the four weeks before. 0.1% of all new papers.