Title: Statistical Analysis of Networks
Authors: Konstantin Avrachenkov and Maximilien Dreveton
Publisher: Now Publishers
ISBN: 978-1-63828-050-7 (Hardcover), 978-1-63828-051-4 (e-book)
Extent: 237 pages
Publication date: 6 October 2022
Available from: http://dx.doi.org/10.1561/9781638280514
Description:
This book is a general introduction to the statistical analysis of networks, and can serve both as
a research monograph and as a textbook. Numerous fundamental tools and concepts needed
for the analysis of networks are presented, such as network modeling, community detection,
graph-based semi-supervised learning and sampling in networks. The description of these
concepts is self-contained, with both theoretical justifications and applications provided for
the presented algorithms. Connections between the approaches to community detection and
the consensus algorithms are explained.
Researchers, including postgraduate students, working in the area of network science,
complex network analysis, or social network analysis, will find up-to-date statistical methods
relevant to their research tasks. This book can also serve as textbook material for courses related
to the statistical approach to the analysis of complex networks.
Table of contents:
- Introduction
- Random graph models
- Network centrality indices
- Community detection in networks
- Graph-based semi-supervised learning
- Community detection in temporal networks
- Sampling in networks
The pdf is freely available from the publisher site.
Hard copies can be ordered from the publisher site or Amazon.
