Point Process Modeling for Directed Interaction Networks
Abstract
Network data often take the form of repeated interactions between senders and receivers tabulated over time. A primary question to ask of such data is which traits and behaviors are predictive of interaction. To answer this question, a model is introduced for treating directed interactions as a multivariate point process: a Cox multiplicative intensity model using covariates that depend on the history of the process. Consistency and asymptotic normality are proved for the resulting partial-likelihood-based estimators under suitable regularity conditions, and an efficient fitting procedure is described. Multicast interactions--those involving a single sender but multiple receivers--are treated explicitly. The resulting inferential framework is then employed to model message sending behavior in a corporate e-mail network. The analysis gives a precise quantification of which static shared traits and dynamic network effects are predictive of message recipient selection.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2011
- Accession Number
- ADA557849
Entities
People
- Patrick J. Wolfe
- Patrick O. Perry
Organizations
- Harvard University