Uncertainty and Networks
Abstract
Networks, or collections of ``nodes and ``ties representing pairwise relations between nodes, can be crucial to understanding social, biological, and physical systems. Many aspects of network modeling are active areas of research, but important gaps remain in the literature. In particular, while methods for causal and statistical inference using data collected on nodes in a social network are rapidly progressing, almost all of them assume that fundamental data on the underlying network are complete and error free. This is unrealistic in all but the most controlled settings, and introduces unacknowledged bias and uncertainty into existing methods. We propose to model and quantify this bias and uncertainty.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 27, 2018
- Source ID
- N000141812760
Entities
People
- Elizabeth L Ogburn
Organizations
- Johns Hopkins University
- Office of Naval Research
- United States Navy