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Algorithms and Dynamical Models for Communities and Reputation in Social Networks / by Vincent Traag
Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Springer Theses, Recognizing Outstanding Ph.D. Research | SpringerLink BücherPublisher: Cham ; Heidelberg ; New York ; Dordrecht ; London : Springer, 2014Description: Online-Ressource (XIV, 229 p. 40 illus., 19 illus. in color, online resource)ISBN:- 9783319063911
- 621
- QC1-QC999
Contents:
Summary: 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 asses 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 linksPPN: PPN: 1657962547Package identifier: Produktsigel: ZDB-2-PHA
Supervisors' Foreword; Preface; Contents; Nomenclature; 1 Introduction; References; Part ICommunities in Networks; 2 Community Detection; 2.1 Modularity; 2.2 Canonical Community Detection; 2.2.1 Reichardt and Bornholdt; 2.2.2 Arenas, Fernández and Gómez; 2.2.3 Ronhovde and Nussinov; 2.2.4 Constant Potts Model; 2.2.5 Label Propagation; 2.2.6 Random Walker; 2.2.7 Infomap; 2.2.8 Alternative Clustering Methods; 2.3 Algorithms; 2.3.1 Simulated Annealing; 2.3.2 Greedy Improvement; 2.3.3 Louvain Method; 2.3.4 Eigenvector; 2.4 Benchmarks; 2.4.1 Test Networks; 2.4.2 Comparing Partitions; 2.4.3 Results
References3 Scale Invariant Community Detection; 3.1 Issues with Modularity; 3.1.1 Resolution Limit; 3.1.2 Non-locality; 3.1.3 Spuriously High Modularity; 3.2 Resolution Limit in Other Models; 3.2.1 RB Model; 3.2.2 AFG Model; 3.2.3 CPM and RN; 3.3 Scale Invariance; 3.3.1 Relaxing the Null Models; 3.3.2 Defining Scale Invariance; References; 4 Finding Significant Resolutions; 4.1 Scanning Resolution Parameter; 4.2 Significance of Partition; 4.2.1 Preliminaries; 4.2.2 Subgraph Probability; 4.2.3 Asymptotic Analysis; 4.2.4 Scanning for Significance; 4.2.5 Optimizing Significance; References
5 Modularity with Negative Links5.1 Social Balance; 5.1.1 Frustration; 5.2 Weighted Models; 5.3 Implementation and Benchmark; References; 6 Applications; 6.1 Communities in International Relations; 6.1.1 Direct Trade and Conflict; 6.1.2 Trading Communities and Conflict; 6.1.3 The Trade Network; 6.1.4 Results; 6.2 Scientific Communities and Negative Links; 6.2.1 Effect of Negative Links; 6.2.2 Dissensus or Specialization?; 6.2.3 A Public Debate; References; Part IISocial Balance and Reputation; 7 Social Balance; 7.1 Balanced Triads; 7.2 Balanced Cycles; 7.3 Weak Social Balance; References
8 Models of Social Balance8.1 Discrete Models; 8.1.1 Local Triad Dynamics; 8.1.2 Constrained Triad Dynamics; 8.2 Continuous Time Squared Model; 8.2.1 Normal Initial Condition; 8.2.2 Generic Initial Condition; 8.3 Continuous Time Transpose Model; 8.3.1 Normal Initial Condition; 8.3.2 Generic Initial Condition; 8.3.3 Genericity; References; 9 Evolution of Cooperation; 9.1 Game Theory; 9.1.1 Finite Population Size; 9.1.2 Fixation Probability for 2 times2 Games; 9.1.3 Infinite Population Size; 9.1.4 Prisoner's Dilemma; 9.2 Towards Cooperation; 9.2.1 Direct Reciprocity; 9.2.2 Indirect Reciprocity
9.3 Private ReputationReferences; 10 Ranking Nodes Using Reputation; 10.1 Ranking Nodes; 10.2 Including Negative Links; 10.3 Convergence and Uniqueness; References; 11 Conclusion; References; Biography of Author; Index
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