Network Analysis

Methodological Foundations

  • Ulrik Brandes
  • Thomas Erlebach

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3418)

Table of contents

  1. Front Matter
  2. Introduction

    1. Ulrik Brandes, Thomas Erlebach
      Pages 1-6
    2. Ulrik Brandes, Thomas Erlebach
      Pages 7-15
  3. Part I Elements

    1. Dirk Koschützki, Katharina Anna Lehmann, Leon Peeters, Stefan Richter, Dagmar Tenfelde-Podehl, Oliver Zlotowski
      Pages 16-61
    2. Riko Jacob, Dirk Koschützki, Katharina Anna Lehmann, Leon Peeters, Dagmar Tenfelde-Podehl
      Pages 62-82
    3. Dirk Koschützki, Katharina Anna Lehmann, Dagmar Tenfelde-Podehl, Oliver Zlotowski
      Pages 83-111
  4. Part II Groups

    1. Sven Kosub
      Pages 112-142
    2. Frank Kammer, Hanjo Täubig
      Pages 143-177
    3. Marco Gaertler
      Pages 178-215
    4. Jürgen Lerner
      Pages 216-252
    5. Marc Nunkesser, Daniel Sawitzki
      Pages 253-292
    6. Michael Brinkmeier, Thomas Schank
      Pages 293-317
    7. Michael Baur, Marc Benkert
      Pages 318-340
    8. Nadine Baumann, Sebastian Stiller
      Pages 341-372
    9. Andreas Baltz, Lasse Kliemann
      Pages 373-416
    10. Gunnar W. Klau, René Weiskircher
      Pages 417-437
  5. Back Matter

About this book


‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models.

From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks.

In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.


Computer Graph theory Internet algorithms applied graph theory combinatorial optimization connectivity graph algorithms graph isomorphisms network algorithms network analysis network design network statistics statistics vertices

Editors and affiliations

  • Ulrik Brandes
    • 1
  • Thomas Erlebach
    • 2
  1. 1.Department of Computer & Information ScienceUniversity of Konstanz 
  2. 2.Department of Computer ScienceUniversity of LeicesterLeicesterUK

Bibliographic information

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