Recovering Network Structure from Aggregated Relational Data using Penalized Regression

Understand

Social network data can be expensive to collect.

• Breza et al.
• (2017) propose aggregated relational data (ARD) as a low-cost substitute that can be used to recover the structure of a latent social network when it is generated by a specific parametric random effects model.
• Our main observation is that many economic network formation models produce networks that are effectively low-rank.