Neural Network Nominate: Mapping Mass Political Ideology via Revealed Preferences [Best Lightning Talk Award]
Cristian Candia presented “Neural Network Nominate (NNN): Mapping Mass Political Ideology via Revealed Preferences” in the lightning-talk session of the Conference on Complex Systems 2025 in Siena, Italy.
The method uses millions of pairwise policy choices to infer the structure of political preferences with an interpretable neural-network architecture, providing an alternative to direct ideological self-placement and traditional legislative scaling approaches.
The presentation received the Best Lightning Talk Award at CCS 2025.
The official CCS programme lists Cristian Candia in the Tuesday, September 2 lightning-talk session, scheduled from 10:30 to 11:00. Each lightning talk lasts three minutes.
Cristian Candia
Associate Professor, Data Science Institute, School of Engineering, Universidad del Desarrollo, Chile. Director of CRiSS-LAB.
Cristian Candia is a computational social scientist studying human and collective behavior with large-scale data, network science, experiments, and AI.