We propose a method to simplify textual Twitter data into understandable networks of terms that can signify important events and their possible changes over time. The method allows for common characteristics of the networks across time periods and each period can comprise multiple unknown sub-networks. The networks are described by Gaussian graphical models and their parameter values ... https://togegmcjay7ozt.theisblog.com/35129799/understanding-extreme-precipitation-scaling-with-temperature-insights-from-multi-spatiotemporal-analysis-in-south-korea