Image credit: CRiSS-LABResumen
This chapter introduces computational social science as a data-driven framework for studying how collective memory forms, persists, and decays. It connects digital archives, social networks, large-scale attention data, and bi-exponential decay models to explain how communicative and cultural memory shape long-term attention.
Publicación
In Cognition, Culture, and Political Momentum: Breaking down the Silos in Collective Memory Research, Oxford University Press
Cristian Candia
Associate Professor and Head of CRiSS-LAB, School of Engineering and School of Government, Universidad del Desarrollo, Chile.
My research interests include collective behavior, collective and artificial intelligence, network science, and business analytics.