دانلود کتاب Complex Networks & Their Applications IX: Volume 1, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020

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Preface Organization and Committees General Chairs Advisory Board Program Chairs Satellite Chairs Lightning Chairs Poster Chairs Publicity Chairs Tutorial Chairs Sponsor Chairs Local Committee Chair Local Committee Publication Chair Web Chair Program Committee Contents Community Structure A Method for Community Detection in Networks with Mixed Scale Features at Its Nodes 1 Introduction: Previous Work and Motivation 2 A Least Squares Criterion 3 Setting of Experiments for Validation and Comparison of SEFNAC Algorithm 3.1 Algorithms Under Comparison 3.2 Datasets 3.3 Evaluation Criteria 4 Results of Computational Experiments 4.1 Parameters of the Generated Datasets 4.2 Validity of SEFNAC 4.3 Comparing SEFNAC and Competition 5 Conclusion References Efficient Community Detection by Exploiting Structural Properties of Real-World User-Item Graphs 1 Introduction 2 Related Work 3 Intuition Behind the Algorithm 4 Model 5 Algorithm 6 Experimental Evaluation 6.1 Evaluation on Detected Communities 6.2 Evaluation on Runtime 6.3 Evaluation on Convergence 7 Conclusions References Measuring Proximity in Attributed Networks for Community Detection 1 Introduction 2 Related Work 3 Background and Preliminaries 3.1 Definitions 3.2 Community Detection Algorithms 3.3 Measures 3.4 Clustering Quality Evaluation 4 Proximity-Based Community Detection in Attributed Networks 5 Experiments 6 Results 7 Conclusion References Core Method for Community Detection 1 Theory 1.1 About Revealing Communities and Key Applied Tasks 1.2 Removing “Garbage” Vertices and Allocating the Core 1.3 Graphs of Information Interaction 1.4 Meta-vertices and Meta-graph 1.5 Core Method 2 Tool 3 An Example of Applying the Method on Data from Twitter 3.1 The Core Detection 3.2 The Structure of Meta-Vertices 4 Conclusions References Effects of Community Structure in Social Networks on Speed of Information Diffusion 1 Introduction 2 Effects of Community Structure on Diffusion Speed of Tweets 2.1 Methodology 2.2 Results 3 Predicting Diffusion Speed 3.1 Problem Setting 3.2 Prediction Method 3.3 Prediction Results 4 Conclusion References Closure Coefficient in Complex Directed Networks 1 Introduction 2 Preliminaries 2.1 Clustering Coefficient 2.2 Closure Coefficient 3 Closure Coefficient in Directed Networks 3.1 Closure Coefficient in Binary Directed Networks 3.2 Closure Coefficients of Particular Patterns 3.3 Closure Coefficient in Weighted Networks 4 Experiments and Analysis 4.1 Directed Closure Coefficient in Real-World Networks 4.2 Link Prediction in Directed Networks 5 Conclusion References Nondiagonal Mixture of Dirichlet Network Distributions for Analyzing a Stock Ownership Network 1 Introduction 2 Related Works 2.1 Sparse Block Model 2.2 Mixture of Dirichlet Network Distributions 3 Nondiagonal Mixture of Dirichlet Network Distributions 3.1 Generating Process 3.2 Inference 4 Results 4.1 Dataset 4.2 Quantitative Comparison 4.3 Estimated Block Structure 5 Conclusion References Spectral Clustering for Directed Networks 1 Introduction 1.1 Motivation 1.2 General Spectral Clustering Algorithm 2 Spectral Clustering for Directed Graphs 3 Simulation Study 4 Congressional Cosponsorship 5 Conclusion References Composite Modularity and Parameter Tuning in the Weight-Based Fusion Model for Community Detection in Node-Attributed Social Networks 1 Introduction 2 WBFM Within ASN CD Problem and Its Logical Gap 2.1 Description of WBFM and Related ASN CD Problem 2.2 WBFM CD Quality Evaluation Process and Its Logical Gap 3 Related Works 4 Theoretical Study 5 Parameter Tuning Scheme 6 Experiments 6.1 Synthetic Node-Attributed Networks 6.2 Real-World Node-Attributed Networks 6.3 Evaluation of the Proposed Parameter Tuning Scheme and Attributes-Aware Modularity 7 Conclusions References Maximal Labeled-Cliques for Structural-Functional Communities 1 Introduction 2 Background: Maximal-Labeled Cliques 3 Community Detection 3.1 Null Model for Labeled-Graphs 3.2 Structural-Functional Divergence 3.3 Structural-Functional Clustering 3.4 Quality of Structural-Functional Clustering 4 Evaluation Results 4.1 SF-Divergence 4.2 Discovering Overlapping Communities 5 Conclusion References Community Detection in a Multi-layer Network Over Social Media 1 Introduction 2 Related Work 2.1 Community Detection Methods in a Multilayer Network 3 Proposed Work 3.1 Dataset 3.2 Proposed Approach 3.3 Network Formulation 4 Results 4.1 Community Detection in Multilayer Network 4.2 Social Network Analysis of Merged User Graph 4.3 Temporal Analysis of User’s Polarity in Network 5 Conclusion References Using Preference Intensity for Detecting Network Communities 1 Introduction 2 A New Approach for Community Detection 3 Preference Relations 4 Preference Relation Properties 5 Framework of the Preference-Based Method 6 Experiments and Results 7 Conclusions and Future Work References Community Detection Algorithm Using Hypergraph Modularity 1 Motivation and Our Contribution 2 Modularity Functions 2.1 Modularity Function for Graphs 2.2 Using Graph Modularity for Hypergraphs 2.3 Modularity Function for Hypergraphs 2.4 Unification and Generalization 3 Algorithms 3.1 Louvain—Graph-Based Algorithm 3.2 Kumar et al.—Refinement of Graph-Based Algorithm 3.3 LS and HA—Our Prototypes 4 Synthetic Random Hypergraph Model 5 Experiments 6 Conclusions and Future Directions References Towards Causal Explanations of Community Detection in Networks 1 Introduction 2 The Causal Model for Community Detection 2.1 Preliminaries 2.2 The Proposed Approach 3 Algorithmic Aspects 3.1 The General Framework 3.2 Working with Modularity-Based Methods 4 Additional Issues and Extensions References A Pledged Community? Using Community Detection to Analyze Autocratic Cooperation in UN Co-sponsorship Networks 1 Motivation 2 Autocratic Cooperation – What We Know and What We Do Not Know 2.1 Scientific Background and Theoretical Argument 2.2 The Missing Piece of the Puzzle 3 Our Approach: Co-sponsorship Networks of UNGA Resolutions 4 Method 5 Results 6 Discussion References Distances on a Graph 1 Introduction 2 Distance, Intra-cluster Density and Graph Clustering (Network Community Detection) 3 Distance Measurements Under Study 3.1 Embedding, Commute and Amplified Commute Distances 3.2 Jaccard Distance 3.3 Otsuka-Ochiai Distance 3.4 Burt's Distance 4 Numerical Comparisons 4.1 Test Data: Synthetic Graphs with Known Clusters 4.2 Empirical Results 4.3 Noise, Sensitivity and Convergence 5 Our Chosen Distance 6 Metric Space and the Jaccard Distance 7 Conclusion References Local Community Detection Algorithm with Self-defining Source Nodes 1 Introduction 2 Related Work 3 Preliminaries and Notation 4 Self-defining Local Community Detection 5 Experimental Analysis 5.1 Evaluating Quality of Communities 5.2 Source Node Selection Analysis 5.3 Computational Complexity Analysis 6 Conclusion and Future Work References Investigating Centrality Measures in Social Networks with Community Structure 1 Introduction 2 Preliminaries and Definitions 2.1 Classical Centrality Measures 2.2 Community-Aware Centrality Measures 3 Datasets and Materials 3.1 Data 3.2 Tools 4 Experimental Results 4.1 Correlation Analysis 4.2 Similarity Analysis 5 Conclusion References Network Analysis Complex Network Analysis of North American Institutions of Higher Education on Twitter 1 Introduction 2 Data Set 3 Network Construction 3.1 A Note on Edge Weight Calculations 4 Network Analysis 4.1 Monadic Analysis 4.2 Dyadic Analysis 4.3 Community Analysis 5 Followers' Analysis 6 Discussion 7 Conclusion References Connectivity-Based Spectral Sampling for Big Complex Network Visualization 1 Introduction 2 Related Work 2.1 Graph Sampling and Spectral Sparsification 2.2 BC (Block Cut-Vertex) Tree Decomposition 2.3 Graph Sampling Quality Metrics 3 BC Tree-Based Spectral Graph Sampling 3.1 Algorithm BC_SS 3.2 Algorithm BC_SV 4 BC_SS and BC_SV Experiments 4.1 Runtime Improvement 4.2 Approximation on the Effective Resistance Values 4.3 Approximation on the Ranking of Edges and Vertices 4.4 Graph Sampling Quality Metrics Comparison 4.5 Jaccard Similarity Index Comparison 4.6 Visual Comparison: SS vs. BC_SS and SV vs. BC_SV 5 Conclusion and Future Work References Graph Signal Processing on Complex Networks for Structural Health Monitoring 1 Introduction 2 Background on GSP 3 Method 3.1 Overview: GSP Methodological Framework 3.2 Dataset 3.3 Network Creation 3.4 Node Subset Selection – Sensor Subset Sampling 4 Results and Discussion 4.1 Sampling: Selecting a Minimal Subset of Sensors 4.2 Network Representation Example: Girders and Deck 4.3 Identification of Mode Shapes 5 Conclusions References An Analysis of Four Academic Department Collaboration Networks with Respect to Gender 1 Introduction 2 Related Works 3 Methods 4 Properties of the Collaboration Network 5 Claims 5.1 Claim: Men Tend to Have More Collaborators 5.2 Claim: Women Tend to Repeatedly Collaborate with the Same Collaborators 5.3 Claim: Researchers Tend to Collaborate with Authors of the Same Gender 5.4 Claim: Women Tend to Collaborate More Intramurally 6 Conclusions and Future Work References Uncovering the Image Structure of Japanese TV Commercials Through a Co-occurrence Network Representation 1 Introduction 2 Methods 3 Results 3.1 Degree and Strength 3.2 Community Structure 4 Discussion References Movie Script Similarity Using Multilayer Network Portrait Divergence 1 Introduction 2 Background 2.1 Extracting Multilayer Networks from Movie Scripts 2.2 Network Comparison Using Portrait and Portrait Divergence 3 Experimental Evaluation 3.1 Comparing Portraits 3.2 Comparing Portrait Divergence 4 Discussion and Conclusion References Interaction of Structure and Information on Tor 1 Introduction 2 Related Work 3 Structural Identity of Tor Domains 3.1 Representation of Tor Structural Identity 3.2 Clustering Tor Structural Identity 4 Conclusion and Future Work References Classifying Sleeping Beauties and Princes Using Citation Rarity*-6pt 1 Introduction 2 Results 2.1 Sleeping Beauties and Princes 2.2 Defining the SB–PR Pair Density 2.3 Density Distribution 2.4 Rediscovering PRs and Exploring PRs 2.5 Relation Type of SBs and Princes 2.6 Density vs. Citation 3 Conclusion 4 Data References Finding High-Degree Vertices with Inclusive Random Sampling 1 Introduction 1.1 Random Neighbor 1.2 Random Edge 1.3 Inclusive Sampling 2 Sampling Method Comparisons 2.1 Calculating the Expectations 2.2 Strengths of RN and RE 2.3 RE/RN and RN/RE Are Both Unbounded 2.4 RE and RN in Trees 3 Sampling Methods in Synthetic and Real-World Graphs 3.1 Synthetic Graphs 3.2 Real-World Networks 4 Inclusive Sampling Methods and Degree Homophily 5 Summary and Future Research Directions References Concept-Centered Comparison of Semantic Networks 1 Introduction 2 Semantic Networks and Concept-Centered Networks 3 Data Description 4 The Choice of the Threshold Value 5 Illustration 6 Concluding Remarks References Diffusion and Epidemics Analyzing the Impact of Geo-Spatial Organization of Real-World Communities on Epidemic Spreading Dynamics 1 Introduction 2 The Geo-Spatial Population Model 2.1 Real Geo-Spatial Data 2.2 Epidemic Reference Data 3 Results 4 Conclusions References Identifying Biomarkers for Important Nodes in Networks of Sexual and Drug Activity 1 Introduction 2 Related Work 3 Methodology 3.1 Data Acquisition and Curation 3.2 Calculating Betweenness Centrality 3.3 Correlation of Features with High Betweenness 4 Results 4.1 Scale-Free Underlying Networks 4.2 City Graphs with High Betweenness Nodes 4.3 Exceptional Attributes per City 4.4 Unique Attributes of High Betweenness Nodes 5 Discussion and Conclusion References Opinion Dynamic Modeling of Fake News Perception 1 Introduction 2 Related Works 3 Fake News: Opinion Dynamic Modeling 4 Experimental Analysis 5 Conclusion References Influence Maximization for Dynamic Allocation in Voter Dynamics 1 Introduction 2 Model Description 3 Results 3.1 Mean-Field Analysis 3.2 Optimal Strategies for Controller A 4 Conclusion References Effect of Interaction Mechanisms on Facebook Dynamics Using a Common Knowledge Model 1 Introduction 1.1 Background and Motivation 1.2 Contributions of This Work 2 Related Work 3 Model 3.1 Preliminaries 3.2 Facebook Common Knowledge Model Mechanisms 4 Social Networks 5 Agent-Based Model and Simulation Parameters 6 Simulation Results 7 Conclusion References Using Link Clustering to Detect Influential Spreaders 1 Introduction 2 Background 2.1 Properties of the Network 3 Approach 3.1 Link Communities 4 Evaluation 4.1 Metrics for Evaluation 4.2 Results 5 Discussion References Prediction of the Effects of Epidemic Spreading with Graph Neural Networks 1 Introduction 2 Related Work 2.1 Analysis of Spreading Processes 2.2 Machine Learning on Networks 3 Task Formulation 4 Proposed Methodology 5 Empirical Evaluation 5.1 Baselines 5.2 Experimental Setting 5.3 Results 5.4 Interpretation of a Prediction 6 Discussion and Conclusions References Learning Vaccine Allocation from Simulations 1 Introduction 2 Related Work 3 Problem Statement 3.1 Continuous-Time Networked SIR Model 3.2 Vaccination Allocation Problem 4 Our Method 4.1 Rejection-Based Simulation 4.2 Impact Score Estimation 4.3 Introducing Simba 4.4 Discussion 4.5 Generalizations 5 Experimental Results 6 Conclusions and Future Work References Suppressing Epidemic Spreading via Contact Blocking in Temporal Networks 1 Introduction 2 Methods 2.1 Link Centrality Metrics 2.2 Contact Removal Probability 2.3 Datasets 2.4 Simulation 3 Results 4 Conclusion and Discussion References Blocking the Propagation of Two Simultaneous Contagions over Networks 1 Introduction 2 Definitions and Analytical Results 3 Experimental Results 4 Future Research Directions References Stimulation Index of Cascading Transmission in Information Diffusion over Social Networks 1 Introduction 2 Related Work 2.1 Information Diffusion Model 2.2 Analysis and Estimation of Information Diffusion 3 Stimulation Index of Cascading Transmission 3.1 Basic Idea of Proposed Method 3.2 Calculation Method 4 Experimental Settings 4.1 Generation of Follow Network 4.2 Simulation of Information Diffusion 5 Experimental Evaluations 5.1 Does Removing the Edge with a High Stimulation Index Inhibit Information Diffusion? 5.2 Is There a Correlation Between the Stimulation Index and the Number of Activations and Activated Nodes? 6 Discussion 7 Conclusion References Diffusion Dynamics Prediction on Networks Using Sub-graph Motif Distribution 1 Introduction 2 Literature 2.1 Motifs and Dynamics on Networks 2.2 Motif Detection Methods Implementations 3 Network Data 4 Method 4.1 Motif Detection Methods 4.2 Subgraph Sampling for Representation of Motifs 4.3 Motifs and Process Spreading: Regression Task Statement 4.4 Self-similarity and Dynamics on Networks 5 Results 5.1 Dynamics on Networks and Motifs 5.2 Sampling Techniques 5.3 Self-similarity and Dynamics 6 Discussion and Conclusion References Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps 1 Introduction 2 Collaborative Risk Map Generation 2.1 Extension of the Consensus Process 2.2 Map Generation 3 Results 3.1 Population and Infection Model 3.2 Risk Map Creation 3.3 Evolution with Contact Tracing App Active 3.4 Contact Tracing and Risk Maps Combined 4 Conclusions References Dynamics on/of Networks Distributed Algorithm for Link Removal in Directed Networks 1 Introduction 2 Problem Statement 2.1 Notation and Premilinaries 2.2 Problem Formulation 3 Main Result 3.1 Distributed Estimation of Dominant Right Eigenvector w0 3.2 Distributed Estimation of Dominant Left Eigenvector 0 3.3 Distributed Verification of Digraph's Strong Connectivity 3.4 The Complete Distributed Link Removal Algorithm 4 An Illustrative Example 5 Conclusion References Data Compression to Choose a Proper Dynamic Network Representation 1 Introduction 2 Context and Motivation 2.1 The Different Models of Dynamic Networks 2.2 Using Encoding Cost as a Selection Criterion 2.3 Applications 3 Temporal Network Encoding Cost 4 Experiments 4.1 Synthetic Networks 4.2 Experiments with Real Networks 5 Conclusion References Effect of Nonisochronicity on the Chimera States in Coupled Nonlinear Oscillators 1 Introduction 2 Swing-By Mechanism and Chimera Death in Coupled Stuart-Landau Oscillators Under Nonlocal Coupling with Symmetry Breaking 2.1 Characterization of Chimera and Other Collective States 2.2 Collective States in the (,c) Parameter Space 3 Conclusion References Evolution of Similar Configurations in Graph Dynamical Systems 1 Introduction 2 Preliminaries 3 Analytical Results 4 Experimental Results 5 Summary and Future Research Directions References Congestion Due to Random Walk Routing 1 Introduction 2 General Results 2.1 Time Evolution Equations 2.2 Steady State Solution 2.3 Discussion 3 Numerical Results 4 Conclusions References Strongly Connected Components in Stream Graphs: Computation and Experimentations 1 The Stream Graph Framework 2 Strongly Connected Components 2.1 Direct Approach 2.2 Fully Dynamic Approach 3 Experiments and Applications 3.1 Datasets 3.2 Algorithm Performances 3.3 Connectedness Analysis of IP Traffic 3.4 Approximate Strongly Connected Components 3.5 Application to Latency Approximation 4 Related Work 5 Conclusion References The Effect of Cryptocurrency Price on a Blockchain-Based Social Network 1 Introduction 2 Steemit: A Blockchain-Based Online Social Network 3 Dataset 4 Methods 5 Results 6 Conclusions References Multivariate Information in Random Boolean Networks 1 Introduction 2 Preliminaries 3 O-Information in Random Boolean Networks 4 Phase Diagram Anatomy 4.1 Ordered Regime 4.2 Critical Point 5 Conclusions References Earth Sciences Applications Complexity of the Vegetation-Climate System Through Data Analysis 1 Introduction 2 Material and Methodology 2.1 Study Case and Plot Selection 2.2 Acquisition of Satellite Data and MSAVI Calculation 2.3 Meteorological Variables 2.4 Date-to-Date Analysis 2.5 Cross-Correlations by Phase 2.6 Recurrence Plots and Recurrence Quantification Analysis 3 Results and Discussion 3.1 Box Plots and Phases Analysis 3.2 Cross-Correlation by Phase 3.3 Differencing Vegetation Index Series and Parameter Optimization 3.4 Recurrence Quantification Analysis 4 Conclusions References Towards Understanding Complex Interactions of Normalized Difference Vegetation Index Measurements Network and Precipitation Gauges of Cereal Growth System 1 Introduction 2 Methods 2.1 Case Study and Data 3 Results 3.1 Analytical Advances of NDVI Cereal Time Series 3.2 Scaling Characteristics of Precipitation Series 4 Conclusions References Spatio-Temporal Clustering of Earthquakes Based on Average Magnitudes 1 Introduction 2 Related Work 2.1 Declustering Algorithms 2.2 Change-Point Detection Algorithms 3 Proposed Method 3.1 Tree Construction Strategies 3.2 Tree Separation Algorithm 4 Experimental Evaluation 4.1 Quantitative Evaluation 4.2 Visual Evaluation 5 Conclusion References Information Spreading in Social Media Analyzing the Robustness of a Comprehensive Trust-Based Model for Online Social Networks Against Privacy Attacks 1 Introduction 2 Background and Related Work 3 The Comprehensive Trust-Based Model 4 Analysis of Attack Scenarios on the Model 4.1 Attack Definitions and Scenario 4.2 Optimizing the Attack: Minimizing the Connections of Fake Users by Reduction from Minimum Vertex Cover 5 Evaluation 6 Discussion, Conclusion, and Future Work References Media Partisanship During Election: Indonesian Cases 1 Introduction 2 Data 3 Method for Political Stance Detection of the Online News Outlets 3.1 Hashtag-Based User Labeling 3.2 Network-Based User Labeling 3.3 Media Classification 4 Analysis 4.1 The Political Stance of News Media Outlets 5 Conclusion References Media Polarization on Twitter During 2019 Indonesian Election 1 Introduction 2 Data 3 Method 3.1 Bipartite Network 3.2 Community Structure 3.3 Political Stance of Online News Media 4 Analysis 4.1 News Consumption Pattern 4.2 Segregation in Media Network 4.3 Political Polarization 4.4 Interaction Across Political Communities 4.5 News Media Centrality 5 Conclusion References Influence of Retweeting on the Behaviors of Social Networking Service Users 1 Introduction 2 Related Works 3 Proposed Model 3.1 Reward Game with Retweeting 3.2 Evolutionary Process in Networked Agents 4 Experiment 4.1 Experimental Settings 4.2 Experimental Results - Complete Graph 4.3 Experimental Results - CNN Networks 4.4 Discussion 5 Conclusion References Author Index