Reconstructing networks / Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini.

Format:

Book

Author/Creator:

Cimini, Giulio, author.

Mastrandrea, Rossana, author.

Squartini, Tiziano, author.

Series:

Cambridge elemets. Elements in structure and dynamics of complex networks 2516-5763

Language:

English

Subjects (All):

System analysis.

Network analysis (Planning).

Information theory.

Statistical physics.

Physical Description:

1 online resource (96 pages) : digital, PDF file(s).

Edition:

1st ed.

Place of Publication:

Cambridge : Cambridge University Press, 2021.

Summary:

Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections.

Contents:

Cover

Title Page

Copyright Page

Reconstructing Networks

Contents

1 Introduction

2 Network Reconstruction at the Macroscale

Macroscale Properties: An Overview

Binary Properties

Weighted Properties

Macroscale Reconstruction of Economic and Financial Networks: A Quick Historical Survey

The Exponential Random Graphs Framework

The Best-Performing Reconstruction Method

Testing Reconstruction at the Macroscale

Quantifying Systemic Risk

3 Network Reconstruction at the Mesoscale

Motifs: The Building Blocks of Networks

Community Structure

The Stochastic Block Model

The Core-Periphery Organization

The Bow-Tie Organization

4 Network Reconstruction at the Microscale

The Link Prediction Framework

Similarity-Based Methods

Model-Based Methods

Hyperbolic Latent Space Models

Network Reconstruction from Noisy Data

Quality Metrics for Link Prediction

5 Conclusions

Appendix A Reconstructing Bipartite Networks

Appendix B Model Selection: A Quick Look at AIC and BIC

References

Disclaimer.

Notes:

Title from publisher's bibliographic system (viewed on 18 Aug 2021).

ISBN:

1-108-80876-X

1-108-77103-3

OCLC:

1263705525