Computational Social Science

Ongoing research on how AI models represent heterogeneous human judgments, preferences, and systematic errors.

Across 1,621,147 observations from Twitter, Reddit and 8chan, overall moral relevance is positively associated with engagement. …

UDD Engineering covered the laboratory’s presentations and academic visits to MIT, Northeastern and Northwestern.

Applied AI and network science initiative that grew from polarization research into dynamic mapping tools for civic debate, organizations, markets, education, and strategic decision-making.

Recent book chapters extend the lab’s work on collective memory, attention, and computational social science.

Why clustering, embeddings, and latent representations matter for studying education, culture, organizations, mobility, and collective behavior.

Education systems are webs of interconnected students, teachers, programs, institutions, and decisions. This chapter argues that a …

Collective memory can be quantified through the collective attention received by cultural icons, artifacts, people, scientific ideas, …

A short essay on why education systems should be studied as networks of students, teachers, programs, and institutions.

This chapter introduces computational social science as a data-driven framework for studying how collective memory forms, persists, and …

UDD Engineering, Corporación Opción and Kids AI Coding discussed technology and children’s wellbeing.

Boundaries of Belonging in Memory, Politics, and School brings together three research areas through complexity science.

Keynote at the Computational Social Science Satellite of the Conference on Complex Systems 2025 in Siena.

Award-winning lightning talk at the Conference on Complex Systems 2025 in Siena, presenting an interpretable neural-network approach to mapping mass political ideology from pairwise policy preferences.

UDD Engineering covered Cristian Candia’s participation at IC2S2 2025, where CRiSS-LAB presented work on computational social science, AI, design capabilities, political ideology, collective memory, and public procurement networks.

Invited faculty participation in the Santa Fe Institute and Universidad de los Andes Complexity Global School in Bogotá.

Course on clustering, dimensionality reduction, representation learning, topic models, anomaly detection, embeddings, and unsupervised workflows for behavioral and social data.

Training in large-scale behavioral data, social networks, experiments, AI, and theory-driven analysis of social systems.

The coverage features work by Adolfo Fuentes, Camila Utreras, Melanie Oyarzún, and Yessica Herrera, who attended with Cristian Candia.

Abstract: [ENG] The unprecedented growth in social media use and large-scale information collection pose new threats, but also offer new opportunities. Modeling and managing complex interactive systems requires the analysis of social and technological signals to gain new insights into human society and individual behavior.

Abstract: [ENG] We discuss two projects that quantify the consequences of our network location for our access to resources and rewards in science. First, we investigate the dynamics of international science through the lens of national citation preferences, introducing a novel measure to characterize these processes and enabling a network analysis of global knowledge production.

How CRiSS-LAB connects collective memory, online engagement, classroom cooperation, educational trajectories, and civic platforms through computational social science.

TXS+ interviewed Cristian Candia about social physics, computational social science, collective memory, identity, and the Lixandria platform.

La Convergencia de las Ciencias Físicas y Sociales: Una Entrevista con el Dr. Cristian Candia En una entrevista reciente, Carla Hermann, Ph.D., la anfitriona del programa Let’s Get Physical, se sentó con el Dr.

Abstract: [ENG] This study seeks to understand how recommender systems can help individuals assemble functionally diverse teams. We run a 2x2 between-subject laboratory experiment with 384 participants to test the effect of a recommender system's algorithms on individuals' teaming experience, team processes, and team performance.

Abstract: [ENG] It is well known that social networks fundamentally impact the dynamic processes of the populations they support. Examples include epidemic outbreaks, the diffusion of innovations, opinion formation, and behavioral evolution.

Abstract: [ENG] Algorithmic matching is a pervasive mechanism in our social and economic lives, used for example in algorithmic job search engines, kidney transplant allocation algorithms, medical residency program allocation, and search engines for finding romantic partners and potential spouses.

This preprint models collective memory as a two-step decay process in which short-lived communicative memory and long-lived cultural …

BioBioChile covered work by Cristian Candia-Castro, César Hidalgo, and Cristián Jara using data and natural language processing to study global fame, public attention, and the number of famous deaths expected in 2017.