GitHub

Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood.

Temporal Exponential Random Graph Models (TERGM) estimated by maximum pseudolikelihood with bootstrapped confidence intervals or Markov Chain Monte Carlo maximum likelihood (MCMC MLE). Goodness of fit ...
RIETI独立行政法人経済産業研究所

How Firms Choose their Partners in the Japanese Supplier-Customer Network? An application of the exponential random graph model

Author Name Hazem KRICHENE (University of Hyogo) / ARATA Yoshiyuki (Fellow, RIETI) / Abhijit CHAKRABORTY (University of Hyogo) / FUJIWARA Yoshi (University of Hyogo) / INOUE Hiroyasu (University of ...
International Monetary Fund

Network Determinants of Cross-Border Merger and Acquisition Decisions

This paper assesses whether cross-border M&A decisions exhibit network effects. We estimate exponential random graph models (ERGM) and temporal exponential random graph models (TERGM) to evaluate the ...
Journal of Medical Internet Research

Framing Pro-Anorexia Discourse on YouTube in South Korea: Social Network and Exponential Random Graph Model Analysis of Video Communities

We further applied exponential random graph models (ERGMs) to assess how channel type, frame, and their interaction influence the formation of ties. Results: The Pro-Ana Advocacy frames were primarily ...
IEEE

Capturing Microdynamics of Temporal Network Growth: An HMM-Based Model of Triadic Closure

Abstract: Complex networks with their nontrivial topological features and rich patterns of interactions are commonly used to model real-world systems, including social networks, biological systems, ...
IEEE

The Temporal Knowledge Graph Reasoning Model Based on Graph Attention Network

Abstract: Temporal knowledge graphs play a crucial role in event prediction and reasoning tasks, but current techniques face challenges in terms of interpretability and capturing complex temporal ...