Data Science and the Dynamics of Collective Memory
Resumen
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
Profesor Asociado, Instituto de Data Science, Facultad de Ingeniería, Universidad del Desarrollo, Chile. Director de CRiSS-LAB.
Cristian Candia es científico social computacional y estudia el comportamiento humano y colectivo usando datos a gran escala, ciencia de redes, experimentos e inteligencia artificial.