Inferring Structure and Forecasting Dynamics on Evolving Networks
Abstract
Networks lie at the heart of social organization and are central to the emergence and perpetuation of adversarial threats. Complex interactions between evolving network topologies and dynamic socio-cultural processes present immense challenges for countering such threats. This interdisciplinary MURI was positioned at the interface between social, mathematical and computational approaches to networks with goals of developing (1) stable metrics for inferring network structures, (2) forecasting dynamical social and information processes on networks, and (3) predicting the outcomes of network interventions. Major progress was made in measuring and modeling spatio-temporal event patterning in relationto network structures, event inference on networks, community detection and classification, processes of network formation, information spread and dynamical games on graphs, and experimental manipulation of social networks in laboratory settings. The MURI was grounded in empirical data on human activity patterns, crime event patterning, social media processes and observations collected through controlled laboratory and online experimental platforms.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 05, 2016
- Accession Number
- AD1001839
Entities
People
- Allon Percus
- Andrea Bertozzi
- Aram Galstyan
- Brinton Milward
- Clayton T. Morrison
- George Tita
- Igor Mezić
- Jeffrey P. Brantingham
- Kristina Lerman
- Michael McBride
- Ronald Breiger
- Yu-han Chang