Analysis and Visualization of Dynamic Networks

TL;DR

This chapter reviews techniques for analyzing and visualizing dynamic networks, highlighting their diverse applications, current research challenges, and recent empirical advancements in the field.

Contribution

It provides a comprehensive overview of existing methods, formal definitions, and recent empirical studies, emphasizing the need for further research in dynamic network analysis.

Findings

Growing applicability across diverse fields

Recent empirical studies with real datasets

Development of foundational theories

Abstract

This chapter provides an overview of the different techniques and methods that exist for the analysis and visualization of dynamic networks. Basic definitions and formal notations are discussed and important references are cited. A major reason for the popularity of the field of dynamic networks is its applicability in a number of diverse fields. The field of dynamic networks is in its infancy and there are so many avenues that need to be explored. From developing network generation models to developing temporal metrics and measures, from structural analysis to visual analysis, there is room for further exploration in almost every dimension where dynamic networks are studied. Recently, with the availability of dynamic data from various fields, the empirical study and experimentation with real data sets has also helped maturate the field. Furthermore, researchers have started to develop foundations and theories based on these datasets which in turn has resulted lots of activity among research communities.