Module 3: Graph Analysis

In module 3 we turn to graph analysis and introduce various measures to understand network structure and dynamics. We begin with fundamental concepts of connectivity and distance, such as geodesic distance and the Largest Connected Component (LCC). The module then covers global metrics used to describe the entire network, including diameter, average path length, density, and mean degree. Following this, several centrality measures are introduced to quantify node influence of individual nodes. These include Eigenvector Centrality, Katz Centrality, and the distinction between Hubs and Authorities for directed networks. The module also explores the concepts of clustering and transitivity, which measure the tendency of nodes to form dense groups. It concludes with an analysis of network resilience, examining the network's ability to maintain structural integrity during random failures or targeted attacks.

Publication Details

Journal
DuEPublico (University of Duisburg-Essen)
Published
2025-10-08
DOI
https://doi.org/10.17185/duepublico/84475
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Module 3: Graph Analysis

DuEPublico (University of Duisburg-Essen)
Complex Network Analysis Techniques
article

Module 3: Graph Analysis

article en

Abstract

In module 3 we turn to graph analysis and introduce various measures to understand network structure and dynamics. We begin with fundamental concepts of connectivity and distance, such as geodesic distance and the Largest Connected Component (LCC). The module then covers global metrics used to describe the entire network, including diameter, average path length, density, and mean degree. Following this, several centrality measures are introduced to quantify node influence of individual nodes. These include Eigenvector Centrality, Katz Centrality, and the distinction between Hubs and Authorities for directed networks. The module also explores the concepts of clustering and transitivity, which measure the tendency of nodes to form dense groups. It concludes with an analysis of network resilience, examining the network's ability to maintain structural integrity during random failures or targeted attacks.

DuEPublico (University of Duisburg-Essen)
Openalex Percentile: Top 46%
Complex Network Analysis Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.