
Complex Networks & Their Applications X
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This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.
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Content
- Intro
- 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
- Network Analysis
- A Fair-Cost Analysis of the Random Neighbor Sampling Method
- 1 Introduction
- 2 RN's Inefficiency for Finding Leaves
- 3 Sampling Costs - Cv and Cn
- 3.1 Critical Cn
- 3.2 CCn for Different Sampling Amounts and Results
- 4 Selection Cost and RVN Sampling
- 4.1 RVN Versus RN
- 5 Fair Cost Analysis
- 5.1 Cost Analysis on the Star Graph
- 5.2 Cost Analysis on BA Graphs
- References
- Analysis of Radiographic Images of Patients with COVID-19 Using Fractal Dimension and Complex Network-Based High-Level Classification
- 1 Introduction
- 2 The Proposed Method
- 2.1 Image Feature Extraction
- 2.2 The Modified High-Level Classification Technique
- 3 Experimental Results
- 3.1 Database
- 3.2 Fractal Feature Extraction
- 3.3 Classification Results
- 4 Conclusions
- References
- Dynamical Influence Driven Space System Design
- 1 Introduction
- 2 Methods
- 2.1 Space System Definition
- 2.2 Data Transfer Capacity Network
- 2.3 Communities of Dynamical Influence
- 2.4 Ground Station Selection
- 3 Results
- 4 Conclusions
- References
- Classification of Dispersed Patterns of Radiographic Images with COVID-19 by Core-Periphery Network Modeling
- 1 Introduction
- 2 Methods
- 3 Experimental Results
- 4 Conclusions
- References
- Small Number of Communities in Twitter Keyword Networks
- 1 Introduction
- 2 Small Community Hypothesis
- 3 Methods and Data
- 3.1 Political Figures
- 3.2 Pseudo-Tweets
- 4 Discussion and Future Work
- References
- Finding Cross-Border Collaborative Centres in Biopharma Patent Networks: A Clustering Comparison Approach Based on Adjusted Mutual Information
- 1 Introduction
- 2 Data and Methods
- 2.1 REGPAT Database
- 2.2 Methods
- 3 Results
- 4 Conclusions
- References
- Professional Judgments of Principled Network Expansions
- 1 Introduction
- 2 Methods
- 2.1 Network Generation
- 2.2 Stimuli
- 2.3 Experiment
- 2.4 Data Analysis
- 3 Results
- 4 Discussion
- 5 Conclusion
- References
- Attributed Graphettes-Based Preterm Infants Motion Analysis
- 1 Introduction
- 2 Materials and Methods
- 2.1 Dataset
- 2.2 Pre-processing: Landmark Points Detection and Filtering
- 2.3 Networks Definition
- 2.4 Attributed Graphettes-Based Representation
- 3 Results: Topics Analysis
- 4 Discussion and Conclusions
- References
- Dynamics of Polarization and Coalition Formation in Signed Political Elite Networks
- Abstract
- 1 Introduction
- 2 Data and Methods
- 3 Result
- 3.1 Cluster Analysis
- 3.2 Polarization Analysis
- 4 Conclusions
- References
- Navigating Multidisciplinary Research Using Field of Study Networks
- 1 Introduction
- 2 Related Work
- 3 Methods
- 3.1 Field of Study Networks
- 3.2 Static FoS Networks
- 3.3 Temporal FoS Networks
- 4 Case Studies
- 4.1 Multidisciplinary Research in Network Science
- 4.2 COVID-19 Research and the Effect on Multidisciplinarity
- 4.3 Close Reading Case Studies in COVID-19 Research
- 5 Conclusions and Future Work
- References
- Public Procurement Fraud Detection: A Review Using Network Analysis
- Abstract
- 1 Introduction
- 2 Method
- 2.1 Bibliometric Analysis and Keyword Search Strategy
- 3 Results
- 3.1 Publications by Author, Number of Citations & Journal/Conference
- 3.2 Major Journals
- 3.3 Conference Proceedings
- 3.4 Analysis of Word Incidence in Sections of Varied Articles
- 3.4.1 Analysis of Keyword Occurrences
- 3.4.2 Author Co-Authorship - Documents and Citations Within Multiple Articles
- 3.4.3 Purpose and Methodology
- 4 Discussion
- 4.1 Scopus and Web of Science Repositories
- 4.2 Research Question RQ1
- 5 Conclusion and Future Studies
- Funding
- References
- Characterising Different Communities of Twitter Users: Migrants and Natives
- Abstract
- 1 Introduction
- 2 Related Works
- 3 Data and Labelling Strategy
- 3.1 Data
- 3.2 Labelling Migrants and Natives
- 4 Twitter Features
- 4.1 Home and Destination Attachment Index
- 4.2 Profile Information
- 4.3 Tweets
- 5 Network Analysis
- 5.1 Properties of the Network
- 5.2 Assortativity Analysis
- 6 Conclusion
- Acknowledgment
- References
- Evolution of the World Stage of Global Science from a Scientific City Network Perspective
- 1 Introduction
- 2 Definitions, Measures and Background
- 2.1 Network Notation and Definitions
- 2.2 Ranking Measures
- 2.3 Rank Comparison Measures
- 3 Materials and Methods
- 3.1 Bibliographic Database
- 3.2 Delineation of Scientific City Agglomerations - Nodes
- 3.3 Publication Sets and Counting Methods - Edge Weights
- 3.4 Network Formation
- 3.5 Evolving Degree Respecting Rewired Networks
- 4 Results
- 4.1 Experimental Setup
- 4.2 Centrality Changes over Time at Various Levels of Impact
- 4.3 Real-World Rank Correlation vs. Null Model
- 4.4 Limitations
- 5 Conclusions
- References
- Propagation on Multi-relational Graphs for Node Regression
- 1 Introduction
- 2 Propagation on Simple Graphs
- 3 Multi-relational Model
- 3.1 Estimation of Relational Parameters
- 3.2 Multi-relational Propagation Algorithm
- 4 Experiments
- 4.1 Multi-relational Estimation of Weather Measurements
- 4.2 Predicting People's Date of Birth in a Social Network
- 5 Conclusion
- References
- Realistic Commodity Flow Networks to Assess Vulnerability of Food Systems
- 1 Introduction
- 1.1 Background and Motivation
- 1.2 Challenges
- 1.3 Contributions
- 1.4 Related Works
- 2 Network Construction Framework
- 2.1 The Senegal Network (SN)
- 2.2 The Nepal Network (NP)
- 3 Network Analysis
- 4 Conclusion
- References
- Structural Network Measures
- PageRank Computation for Higher-Order Networks
- 1 Introduction
- 2 Related Works
- 3 Variable-Order Network Representation
- 4 Application of PageRank to Variable-Order Networks
- 5 Datasets and Experimental Settings
- 6 Results
- 7 Future Works
- References
- Fellow Travelers Phenomenon Present in Real-World Networks
- 1 Introduction
- 2 Basic Notions and Notations
- 3 Theoretical Results
- 4 Interval Leanness in Real-World Networks
- References
- The Fréchet Mean of Inhomogeneous Random Graphs
- 1 Introduction
- 1.1 Our Main Contributions
- 2 Main Results
- 2.1 The Population Fréchet Mean Graph of G(n,P)
- 2.2 The Sample Fréchet Mean Graph of a Graph Sample in G(n,P)
- 3 Proofs of the Main Results
- 3.1 The Population and sample Fréchet Functions
- 3.2 Proof of Theorem 1
- 3.3 The Sample Fréchet Function for the Hamming Distance
- 3.4 Concentration of the Sample Fréchet Function
- 3.5 Proof of Theorem 2
- 4 Simulation Studies
- 5 Discussion and Conclusion
- References
- A Simple Extension of the Bag-of-Paths Model Weighting Path Lengths by a Poisson Distribution
- 1 Introduction
- 1.1 General Introduction
- 1.2 Contributions and Contents of the Paper
- 2 The Standard Randomized Shortest Paths and Bag-of-Paths Models
- 2.1 The Standard Randomized Shortest Paths Model
- 2.2 The Standard Bag-of-Paths Model
- 3 Bag-of-Paths with Weights on Path Lengths
- 3.1 A Poisson Distribution on path Lengths
- 3.2 Computing the Joint Probability of Drawing a Path Starting in i and Ending in j
- 3.3 A Derived Distance Measure Between Nodes
- 3.4 Weighting Start and end Nodes
- 4 Experiments
- 4.1 Datasets
- 4.2 Investigated State-of-the-Art Methods
- 4.3 Experimental Design
- 4.4 Results and discussion
- 5 Conclusion and further Work
- References
- Spectral Rank Monotonicity on Undirected Networks
- 1 Introduction
- 2 Graph-Theoretical Preliminaries
- 3 Score and Rank Monotonicity Axioms on Undirected Graphs
- 4 Eigenvector Centrality
- 5 Seeley's Index
- 6 Graph Fibrations and Spectral Ranking
- 7 PageRank
- 8 Experiments on IMDB
- 9 Conclusions
- References
- Learning Centrality by Learning to Route
- 1 Introduction
- 2 Related Work
- 3 Background
- 4 Methods
- 4.1 The Eigenvector RBC Algorithm
- 4.2 Direct Optimization of the Routing Policy
- 4.3 Learning the Routing Function from Node Embedding
- 5 Evaluation
- 5.1 Experimental Setup
- 5.2 Results
- 6 Conclusion
- References
- On the Exponential Ranking and Its Linear Counterpart
- 1 Introduction
- 2 Problem Statement
- 2.1 Necessary Facts from Graph Theory
- 2.2 Ranking and Scoring
- 3 Two Ranking Schemes for Signed Graphs
- 3.1 Exponential Ranking
- 3.2 Quasi-exponential Ranking
- 4 Numerical Analysis
- 5 Conclusions
- References
- FPPR: Fast Pessimistic PageRank for Dynamic Directed Graphs
- 1 Introduction
- 2 Related Work
- 3 Proposed Fast Pessimistic PageRank (FPPR) Algorithm for Dynamic Directed Graphs
- 4 Experiments and Results
- 4.1 Results
- 4.2 Computation Complexity
- 5 Conclusion
- References
- Community Structure
- An Extension of K-Means for Least-Squares Community Detection in Feature-Rich Networks
- 1 Introduction: Background and Motivation
- 2 Least-Squares Criterion and Extended K-means
- 2.1 Least Squares Model for Community Detection
- 2.2 The Alternating Minimization and K-means
- 2.3 A Formulation Using Cosine Distance
- 3 Experimental Setting
- 4 Experimental Results
- 4.1 Comparison at Real-World Datasets
- 4.2 Comparison at Synthetic Datasets with Categorical Features
- 5 Conclusion
- References
- 515443_1_En_25_Chapter_OnlinePDF
- Selecting Informative Features for Post-hoc Community Explanation
- 1 Introduction
- 2 Background and Related Work
- 3 Methodology
- 3.1 Graph Generation
- 3.2 Community Detection
- 3.3 Network Features
- 3.4 Graph Rewiring
- 3.5 Community Classification
- 3.6 Statistical Methodology and Pilot Study
- 4 Results and Discussion
- 5 Conclusion
- References
- 515443_1_En_26_Chapter_OnlinePDF
- Community Detection by Resistance Distance: Automation and Benchmark Testing
- 1 Introduction
- 2 Methods
- 2.1 Definitions and Notation
- 2.2 Resistance-Distance-Based Community Detection Method
- 2.3 Method Validation: Benchmark Testing and Accuracy
- 3 Results
- 4 Discussion and Conclusion
- References
- 515443_1_En_27_Chapter_OnlinePDF
- Analysis of the Co-authorship Sub-networks of Italian Academic Researchers
- 1 Introduction
- 2 Dataset and Networks Description
- 3 Results
- 3.1 Topological Analysis
- 3.2 Community Analysis
- 4 Conclusions and Future Work
- References
- 515443_1_En_28_Chapter_OnlinePDF
- Dissecting Graph Measure Performance for Node Clustering in LFR Parameter Space
- 1 Introduction
- 2 Definitions
- 2.1 Kernel k-means
- 2.2 Closeness Measures
- 3 Dataset
- 4 Results
- 4.1 Global Leadership in LFR Space
- 4.2 Feature Importance Study
- 4.3 Gaussian Filter in Feature Space
- 5 Conclusions
- References
- 515443_1_En_29_Chapter_OnlinePDF
- Analyzing Community-Aware Centrality Measures Using the Linear Threshold Model
- 1 Introduction
- 2 Community-Aware Centrality Measures
- 3 Linear Threshold Model
- 4 Datasets and Evaluation Process
- 4.1 Data
- 4.2 Evaluation Process
- 5 Diffusive Power of the Community-aware Centrality Measures
- 5.1 Comparing the Outbreak Size with a Low Threshold
- 5.2 Comparing the Outbreak Size with a High Threshold
- 5.3 Comparing the Outbreak Size with a Random Threshold Uniformly Distributed
- 6 Ranking the Centrality Measures
- 7 Discussion
- 8 Conclusion
- References
- 515443_1_En_30_Chapter_OnlinePDF
- CoVerD: Community-Based Vertex Defense Against Crawling Adversaries
- 1 Introduction
- 2 Related Work
- 2.1 Defense via Local Network Perturbations
- 2.2 Defense via Global Network Perturbations
- 3 Preliminaries and Problem Definition
- 4 Method
- 4.1 CoVerD Algorithm
- 5 Experiments
- 5.1 Results
- 6 Conclusion and Future Direction
- References
- 515443_1_En_4_PartFrontmatter_OnlinePDF
- Link Analysis and Ranking
- 515443_1_En_31_Chapter_OnlinePDF
- wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction
- 1 Introduction
- 2 Formulation
- 3 Results
- 3.1 Dataset
- 3.2 Sign Prediction
- 3.3 Weight Prediction
- 3.4 Signed Weight Prediction
- 3.5 Code Availability
- 4 Conclusions
- References
- 515443_1_En_32_Chapter_OnlinePDF
- Link Predictability Classes in Complex Networks
- 1 Introduction
- 2 Related Works
- 3 Problem Statement and the Proposed Pipeline
- 4 Experimental Study
- 4.1 Synthetic Networks
- 4.2 Real-World Networks
- 5 Conclusions and Future Work
- References
- 515443_1_En_33_Chapter_OnlinePDF
- Vertex Entropy Based Link Prediction in Unweighted and Weighted Complex Networks
- 1 Introduction
- 2 Problem Statement and Related Work
- 2.1 Related Work
- 3 Preliminaries and Algorithm Framework
- 3.1 Preliminaries
- 3.2 Proposed Algorithm Framework
- 4 Experimental Setup and Result Analysis
- 4.1 Evaluation Metrics
- 4.2 Datasets
- 4.3 Results and Discussion
- 5 Conclusion
- References
- 515443_1_En_5_PartFrontmatter_OnlinePDF
- Network Models
- 515443_1_En_34_Chapter_OnlinePDF
- Population Dynamics and Its Instability in a Hawk-Dove Game on the Network
- Abstract
- 1 Introduction
- 2 Materials and Methods
- 2.1 Agents and Space
- 2.2 Model Description
- 2.3 Parameter Settings
- 3 Results
- 4 Conclusion
- References
- 515443_1_En_35_Chapter_OnlinePDF
- Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning
- Abstract
- 1 Introduction
- 2 Background Literature
- 3 The Self-modeling Network Modeling Approach Used
- 4 The Adaptive Network Model for Organisational Learning
- 5 Example Simulation Scenario
- 6 Discussion
- References
- 515443_1_En_36_Chapter_OnlinePDF
- A Leading Author Model for the Popularity Effect on Scientific Collaboration
- 1 Introduction
- 2 Model
- 3 Algorithm
- 3.1 Preliminary
- 3.2 Likelihood Function
- 3.3 Gibbs Sampling
- 3.4 EM Algorithm
- 3.5 Inference
- 4 Real Data Analysis
- 4.1 Scientific Collaboration Data
- 4.2 Popularity Effect
- 4.3 Influential Author Finding
- 5 Concluding Remark
- References
- 515443_1_En_37_Chapter_OnlinePDF
- Factoring Small World Networks
- 1 Introduction
- 2 Related Work
- 3 Definitions
- 3.1 Small Worlds
- 3.2 Thresholding Limitations
- 3.3 Problem Definition
- 4 Detection Process
- 4.1 Detection Using Undirected Weights
- 4.2 Guarantee of Detecting Strong Links in SW2
- 4.3 Guarantee of Detecting Weak Links in SW2
- 4.4 Effect of Random Links on Strong Links in SW2
- 4.5 Complexity
- 5 Experiments
- 5.1 Data Sets, Algorithms and Methods
- 5.2 Exposing the Regular Network
- 5.3 Effectively Identifying Strong and Weak Links
- 5.4 Evidence for Effectiveness of Vett
- 6 Conclusion
- References
- 515443_1_En_38_Chapter_OnlinePDF
- Limitations of Chung Lu Random Graph Generation
- 1 Introduction
- 1.1 Our Contributions
- 2 Properties of the Matrix Model
- 2.1 Not All Solutions are Positive
- 3 Results
- 4 Conclusion
- References
- 515443_1_En_39_Chapter_OnlinePDF
- Surprising Behavior of the Average Degree for a Node's Neighbors in Growth Networks
- 1 Introduction
- 2 Barabási-Albert model
- 2.1 Notations
- 2.2 The Evolution of the Barabási-Albert networks
- 3 The Dynamics of i(t)
- 3.1 The Main Result
- 3.2 Empirical Results
- 4 Conclusion
- A The Proof of Lemma 1
- B The Proof of Lemma 2
- References
- 515443_1_En_40_Chapter_OnlinePDF
- Towards Building a Digital Twin of Complex System Using Causal Modelling
- 1 Introduction
- 2 Prerequisites
- 2.1 Structural Causal Models
- 2.2 Noisy-OR
- 3 Causal Modelling for a Digital Twin
- 3.1 Digital Twin Architecture
- 3.2 Defining Variables and Rules
- 3.3 Noisy-OR SCM Models
- 3.4 Model Discovery from Observable Data
- 4 Experiments
- 4.1 Setup
- 4.2 Results
- 5 Conclusions
- References
- 515443_1_En_41_Chapter_OnlinePDF
- Constructing Weighted Networks of Earthquakes with Multiple-parent Nodes Based on Correlation-Metric
- 1 Introduction
- 2 Related Work
- 2.1 Link-Based Declustering Approach
- 2.2 k-Nearest Neighbors Approach
- 3 Proposed Method
- 3.1 Network Construction
- 3.2 Link-Weight Assignment
- 4 Experimental Evaluation
- 5 Conclusion
- References
- 515443_1_En_6_PartFrontmatter_OnlinePDF
- Motif Discovery in Complex Networks
- 515443_1_En_42_Chapter_OnlinePDF
- Motif-Role Extraction in Uncertain Graph Based on Efficient Ensembles
- 1 Introduction
- 2 Related Work
- 3 Problem Framework
- 3.1 Motif Based Role Extraction
- 3.2 Role Extraction from Uncertain Graph
- 4 Methodology
- 4.1 Graph Ensemble
- 4.2 Role-Vector Ensemble
- 4.3 Similarity Ensemble
- 4.4 Cluster Ensemble
- 5 Experimental Evaluations
- 5.1 Dataset and Settings
- 5.2 Similarity Evaluation of Estimated Role Vectors
- 5.3 Similarity Evaluation of Estimated Similarity Matrices
- 5.4 Similarity Evaluation of Estimated Clusters
- 5.5 Efficiency Evaluation
- 5.6 Characteristic Evaluation of Extracted Roles
- 6 Conclusion
- References
- 515443_1_En_43_Chapter_OnlinePDF
- Analysing Ego-Networks via Typed-Edge Graphlets: A Case Study of Chronic Pain Patients
- 1 Introduction
- 2 Background and Preliminaries
- 2.1 Graphlets
- 2.2 Egocentric Graphlets
- 3 Typed-Edge Graphlet Degree Vector
- 4 Experiments and Analysis
- 4.1 Dataset
- 4.2 Analysing Pain Grades via GDV and TyE-GDV
- 4.3 Predicting Pain Grades via GDV and TyE-GDV
- 5 Conclusion
- References
- 515443_1_En_44_Chapter_OnlinePDF
- Analyzing Escalations in Militarized Interstate Disputes Using Motifs in Temporal Networks
- Abstract
- 1 Introduction
- 2 Materials and Methods
- 3 Results
- 3.1 Motifs of Interest
- 3.2 Temporal Motif Distributions at Different Completion Times
- 3.3 Motif Distributions Over Time and States
- 4 Conclusion
- Acknowledgments
- References
- 515443_1_En_45_Chapter_OnlinePDF
- Experiments on F-Restricted Bi-pattern Mining
- 1 Introduction
- 2 F-Restricted Bi-pattern Mining
- 2.1 Core Closed Single Pattern Mining
- 2.2 Core Closed Bi-pattern Mining
- 2.3 F-Restricted Core-Closed Bi-pattern Mining
- 2.4 Restricted Bi-Pattern Enumeration
- 3 Experiments
- 3.1 First Experiments on Restricted Bi-patterns Mining
- 3.2 Qualitative Experiments on F-Restricted Bi-pattern Mining
- 4 Conclusion
- References
- 515443_1_En_7_PartFrontmatter_OnlinePDF
- Temporal Networks
- 515443_1_En_46_Chapter_OnlinePDF
- Finding Colorful Paths in Temporal Graphs
- 1 Introduction
- 2 Preliminaries
- 3 Inapproximability of Max CPTG
- 4 A Heuristic for Max CPTG
- 5 Experimental Results
- 6 Conclusion
- References
- 515443_1_En_47_Chapter_OnlinePDF
- Quantitative Evaluation of Snapshot Graphs for the Analysis of Temporal Networks
- 1 Introduction
- 2 Related Works
- 3 Proposed Evaluation Framework
- 3.1 Stability
- 3.2 Fidelity
- 4 Filtering Procedure
- 5 Results
- 5.1 Datasets
- 5.2 Stochastic Baseline
- 5.3 Stability of Filtered and Aggregated Networks
- 5.4 Fidelity: FPs vs FNs
- 6 Conclusions
- 6.1 Discussion
- 6.2 Alternatives and Future Perspectives
- References
- 515443_1_En_48_Chapter_OnlinePDF
- Convergence Properties of Optimal Transport-Based Temporal Networks
- 1 Introduction
- 2 The Model
- 2.1 Network Sequences
- 3 Results on Synthetic Data
- 3.1 Results on Real Networks of P. polycephalum
- 4 Conclusions
- 1 Synthetic Data
- 2 P. polycephalum Networks
- References
- 515443_1_En_49_Chapter_OnlinePDF
- A Hybrid Adjacency and Time-Based Data Structure for Analysis of Temporal Networks
- 1 Introduction
- 2 Background and Related Work
- 2.1 Temporal Network Representations
- 2.2 Data Structures for Networks
- 2.3 Related Work
- 3 Proposed Hybrid Data Structure
- 3.1 Interval Tree: Time-Based Slices
- 3.2 Adjacency Dictionary: Node-Based Slices
- 3.3 Compound Slices
- 4 Experiments
- 4.1 Data Sets
- 4.2 Comparison Baselines
- 4.3 Basic Operations
- 4.4 Case Study
- 5 Results
- 5.1 Basic Operations
- 5.2 Case Study
- 6 Conclusion
- References
- 515443_1_En_8_PartFrontmatter_OnlinePDF
- Modeling Human Behavior
- 515443_1_En_50_Chapter_OnlinePDF
- Markov Modulated Process to Model Human Mobility
- 1 Introduction
- 2 Random Mobility Simulator
- 3 The Markov Modulated Process (MMP)
- 3.1 A First Approach: the Combinatorial MMP Model
- 3.2 Reduced MMP Model for Human Mobility
- 4 Real-world Application of MMP to HMP in a Library
- 4.1 Building the Reduced MMP Model
- 4.2 Results of the Reduced MMP Model
- 5 Conclusions and Outlook
- References
- 515443_1_En_51_Chapter_OnlinePDF
- An Adaptive Mental Network Model for Reactions to Social Pain
- Abstract
- 1 Introduction
- 2 Background Literature
- 3 Modeling Adaptive Networks
- 4 An Adaptive Network Model for Reactions to Social Pain
- 5 Simulation Results
- 6 Discussion
- References
- 515443_1_En_52_Chapter_OnlinePDF
- Impact of Monetary Rewards on Users' Behavior in Social Media
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 3.1 SNS-Norms Game with Monetary Reward and Article Quality
- 3.2 Evolutionary Process
- 4 Experiments
- 4.1 Experimental Settings
- 4.2 Experimental Result - Complete Graph
- 4.3 Experimental Results - CNN-Model Network
- 5 Conclusion
- References
- 515443_1_En_53_Chapter_OnlinePDF
- Versatile Uncertainty Quantification of Contrastive Behaviors for Modeling Networked Anagram Games
- 1 Introduction
- 1.1 Background and Motivation
- 1.2 Our Contributions and Their Implications
- 2 Related Work
- 3 Previous Models
- 4 The Proposed VUQ Method
- 5 Model Evaluation
- 6 Simulations and Results
- 6.1 Simulation Parameters and Process
- 6.2 Simulation Results
- 7 Conclusion
- References
- 515443_1_En_54_Chapter_OnlinePDF
- Neural-Guided, Bidirectional Program Search for Abstraction and Reasoning
- 1 Introduction
- 2 Abstraction Using DreamCoder
- 2.1 Warmup: Forming Abstractions
- 2.2 Enabling Generalization on ARC Symmetry Tasks
- 2.3 Discussion
- 3 Bidirectional, Neural-Guided Program Search
- 3.1 Algorithm Description
- 3.2 Experiments
- 4 Discussion
- References
- 515443_1_En_55_Chapter_OnlinePDF
- Success at High Peaks: A Multiscale Approach Combining Individual and Expedition-Wide Factors
- 1 Data
- 2 The Effect of Climbing with Repeat Partners
- 3 Intra-expedition Features Determining Success
- 4 Generating a Multiscale Network
- 5 Determining Layer Importance Through Correlation with Success
- 6 Community Detection to Identify Patterns of Success
- 7 Discussion and Future Work
- References
- 515443_1_En_56_Chapter_OnlinePDF
- Data-Driven Modeling of Evacuation Decision-Making in Extreme Weather Events
- 1 Introduction
- 1.1 Background and Motivation
- 1.2 Our Contributions
- 2 Models and Results
- 2.1 Network Model
- 2.2 Family Behavior Model
- 2.3 Agent-Based Model for Simulation
- 3 Simulations and Results
- 3.1 Simulation Description and Parameters
- 3.2 Simulation Results
- 3.3 Policy Implications of Results
- 4 Conclusions
- References
- 515443_1_En_57_Chapter_OnlinePDF
- Effects of Population Structure on the Evolution of Linguistic Convention
- 1 Introduction
- 2 Model
- 2.1 Model Definition
- 2.2 Network Topologies
- 3 Results
- 3.1 Influence of Population Structure
- 3.2 Influence of Population Size
- 4 Conclusions
- References
- 515443_1_En_58_Chapter_OnlinePDF
- Quoting is not Citing: Disentangling Affiliation and Interaction on Twitter
- References
- 515443_1_En_9_PartFrontmatter_OnlinePDF
- Network in Finance and Economics
- 515443_1_En_59_Chapter_OnlinePDF
- The COVID-19 Pandemic and Export Disruptions in the United States
- 1 Introduction
- 2 Theory
- 2.1 Industry Linkages and Disruption Propagation
- 2.2 Effectiveness of Policy Interventions
- 3 Data and Research Design
- 3.1 Covariates
- 3.2 Model and Specification: The Count ERGM
- 4 Results
- 5 Conclusion
- References
- 515443_1_En_60_Chapter_OnlinePDF
- Default Prediction Using Network Based Features
- 1 Introduction
- 2 Temporal Transactional Network
- 3 Prediction Method
- 3.1 Financial Features
- 3.2 Network Features
- 3.3 High Class Imbalance Problem
- 3.4 Classifiers
- 4 Performance Analysis
- 4.1 Experimental Setup
- 4.2 Preliminary Selection of Classifier and Class Imbalance Method
- 4.3 Comparison Between Models
- 4.4 Robustness of the Optimal Model
- 4.5 Interpretation of Results
- 5 Conclusions and Future Work
- References
- 515443_1_En_61_Chapter_OnlinePDF
- Can You Always Reap What You Sow? Network and Functional Data Analysis of Venture Capital Investments in Health-Tech Companies
- 1 Introduction
- 2 Network Characterization
- 2.1 Communities
- 3 Success Analysis
- 4 Discussion
- References
- 515443_1_En_62_Chapter_OnlinePDF
- Asymmetric Diffusion in a Complex Network: The Presence of Women on Boards
- 1 Introduction
- 2 Theoretical Framework
- 2.1 Dynamical Processes on an Undirected Network
- 2.2 Asymmetric Agreement
- 2.3 Asymptotics
- 3 A Real Network: Boards of Directors and the Proportion of Women on Boards
- 3.1 Network of Company Boards
- 3.2 Empirical Symmetric Model
- 3.3 Empirical Asymmetric Model
- 4 Conclusions
- References
- 515443_1_En_63_Chapter_OnlinePDF
- Marginalisation and Misperception: Perceiving Gender and Racial Wage Gaps in Ego Networks
- 1 Introduction
- 2 Related Literature
- 3 Model
- 4 Results
- 4.1 Mean Local Perceptions
- 4.2 Individual Local Perceptions
- 4.3 Composite Signal and Empirical Calibration
- 5 Discussion
- References
- 515443_1_En_64_Chapter_OnlinePDF
- A Networked Global Economy: The Role of Social Capital in Economic Growth
- 1 Introduction
- 2 Materials and Methods
- 2.1 Network Centralities as Proxy for Types of Social Capital
- 2.2 Link Between Social Capital Types and TFP Factors
- 2.3 Social Capital and Economic Growth
- 2.4 Global Network Data
- 3 Results
- 3.1 Panel Data Set
- 3.2 Social Capital Contribution to Economic Output
- 4 Conclusions
- References
- 515443_1_En_65_Chapter_OnlinePDF
- The Role of Smart Contracts in the Transaction Networks of Four Key DeFi-Collateral Ethereum-Based Tokens
- 1 Introduction
- 1.1 Blockchain and Ethereum
- 1.2 Transaction Networks in Blockchain Systems
- 1.3 Four Tokens Used as DeFi Collateral
- 2 Data Description
- 2.1 Preferential Attachment
- 3 Methods and Implementation
- 3.1 Network Dismantling
- 3.2 Assortativity
- 4 Discussion
- References
- 515443_1_En_10_PartFrontmatter_OnlinePDF
- Resilience, Synchronization and Control
- 515443_1_En_66_Chapter_OnlinePDF
- Synchronization of Complex Networks Subject to Impulses with Average Characteristics
- 1 Introduction
- 2 Preliminaries
- 3 Main Results
- 4 Example
- 5 Conclusion
- References
- 515443_1_En_67_Chapter_OnlinePDF
- Retrieval of Redundant Hyperlinks After Attack Based on Hyperbolic Geometry of Web Complex Networks
- Abstract
- 1 Introduction
- 2 Methods and Evaluation Metrics
- 2.1 Problem Definition
- 2.2 Attack Strategies
- 2.3 Retrieval Strategies
- 2.4 Redundant Hyperlinks Identification
- 2.5 Evaluation Metrics
- 3 Datasets
- 4 Experimental Results and Analysis
- 4.1 Comparison of Retrieval Methods
- 4.2 Comparison of the Network Structure Under Different Retrieval Strategy
- 5 Conclusion
- References
- 515443_1_En_68_Chapter_OnlinePDF
- Deep Reinforcement Learning for FlipIt Security Game
- 1 Introduction
- 2 Related Work
- 3 Game Environment
- 3.1 Framework
- 3.2 Markov Decision Process
- 4 Model Architecture
- 5 Experimental Results
- 5.1 Renewal Strategies
- 5.2 Larger Action-Spaced FlipIt Extension
- 5.3 Multiplayer FlipIt
- 5.4 Future Work
- 6 Conclusion
- References
- 515443_1_En_69_Chapter_OnlinePDF
- Accelerating Opponent Strategy Inference for Voting Dynamics on Complex Networks
- 1 Introduction
- 2 Model Description
- 3 Results
- 3.1 Inferring the Opponent Strategy at a Single Node
- 3.2 Inferring Opponent Strategies over Entire Networks
- 4 Conclusion
- References
- 515443_1_En_70_Chapter_OnlinePDF
- Need for a Realistic Measure of Attack Severity in Centrality Based Node Attack Strategies
- 1 Introduction
- 2 Centrality Based Attack Strategies
- 2.1 Random (Rand) Attacks
- 2.2 Degree Centrality (DC) Attacks
- 2.3 Betweenness Centrality (BC)
- 2.4 Combination of Degree and Betweenness Centrality
- 2.5 Eigenvector Centrality (EC) Attacks
- 2.6 Closeness Centrality (CC) Attacks
- 3 Efficiency Measures
- 3.1 Size of Largest Connected Component (LCC)
- 3.2 Average Geodesic Path Length
- 4 A Comparative Study of Centrality Based Attack Strategies
- 5 Conclusions
- References
- 515443_1_En_71_Chapter_OnlinePDF
- Mixed Integer Programming and LP Rounding for Opinion Maximization on Directed Acyclic Graphs
- 1 Introduction
- 1.1 Related Work
- 2 Preliminaries
- 2.1 Opinion Formation Games
- 2.2 Opinion Maximization
- 3 Mixed Integer Programming and LP Rounding for Directed Acyclic Graphs
- 3.1 Mixed Integer Linear Programs
- 3.2 LP Randomized Rounding Algorithms
- 4 Numerical Results for LP Randomized Rounding 1
- 4.1 Directed Trees
- 4.2 Directed Acyclic Graphs
- 5 Conclusions and Future Work
- References
- 515443_1_En_72_Chapter_OnlinePDF
- Correction to: Complex Networks & Their Applications X
- Correction to: R. M. Benito et al. (eds.): Complex Networks & Their Applications X, SCI 1072, https://doi.org/10.1007/978-3-030-93409-5
- Author Index
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