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Algorithms and Dynamical Models for Communities and Reputation in Social Networks

  • Book
  • © 2014

Overview

Authors:
  1. Vincent Traag

    1. KITLV, Leiden, The Netherlands

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  • Nominated as an Outstanding Ph.D. thesis by Catholic University of Louvain, Belgium
  • Provides both introductory and advanced material for community detection
  • Uniquely connects social balance to the evolution of cooperation
  • Integrates both theoretical and empirical perspectives
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Theses (Springer Theses)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction

    • Vincent Traag
    Pages 1-7

  3. Communities in Networks

    1. Front Matter

      Pages 9-9
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    2. Community Detection

      • Vincent Traag
      Pages 11-47

    3. Scale Invariant Community Detection

      • Vincent Traag
      Pages 49-74

    4. Finding Significant Resolutions

      • Vincent Traag
      Pages 75-92

    5. Modularity with Negative Links

      • Vincent Traag
      Pages 93-101

    6. Applications

      • Vincent Traag
      Pages 103-126

  4. Social Balance and Reputation

    1. Front Matter

      Pages 127-127
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    2. Social Balance

      • Vincent Traag
      Pages 129-141

    3. Models of Social Balance

      • Vincent Traag
      Pages 143-172

    4. Evolution of Cooperation

      • Vincent Traag
      Pages 173-210

    5. Ranking Nodes Using Reputation

      • Vincent Traag
      Pages 211-222

    6. Conclusion

      • Vincent Traag
      Pages 223-224

  5. Back Matter

    Pages 225-229
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Keywords

About this book

A persistent problem when finding communities in large complex networks is the so-called resolution limit. This thesis addresses this issue meticulously, and introduces the important notion of resolution-limit-free. Remarkably, only few methods possess this desirable property, and this thesis puts forward one such method. Moreover, it discusses how to assess whether communities can occur by chance or not. One aspect that is often ignored in this field is treated here: links can also be negative, as in war or conflict. Besides how to incorporate this in community detection, it also examines the dynamics of such negative links, inspired by a sociological theory known as social balance. This has intriguing connections to the evolution of cooperation, suggesting that for cooperation to emerge, groups often split in two opposing factions. In addition to these theoretical contributions, the thesis also contains an empirical analysis of the effect of trading communities on international conflict, and how communities form in a citation network with positive and negative links.

Authors and Affiliations

  • KITLV, Leiden, The Netherlands

    Vincent Traag

About the author

After having obtained a (cum laude) Masters in sociology from the University of Amsterdam, Vincent Traag turned to the Université catholique de Louvain in Belgium, where he obtained his Ph.D. in applied mathematics, under the supervision of Paul Van Dooren and Yurii Nesterov. Trying to combine sociology and mathematics, Traag performed extensive research in complex networks, with a particular focus on communities and reputation in networks. One particular interest is how conflict and cooperation arise. In his current position Traag is trying to understand how elite networks in Indonesia reflect political events.

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