
Complex Networks and Their Applications VII
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Content
- Intro
- Preface
- Organization and Committees
- General Chairs
- Advisory Board
- Program Co-chairs
- Poster Chairs
- Lightning Chairs
- Media and Publicity Chairs
- Tutorial Chairs
- Local Chairs
- Local Committee
- Publication Chair
- Submission Chair
- Web Chair
- Program Committee
- Contents
- Network Analysis
- A Software to Extract Criminal Networks from Unstructured Text in Spanish
- the Case of Peruvian Criminal Networks
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Problem Statement
- 4 The Proposed Tool to Extract Criminal Networks
- 5 Analysing a Peruvian Criminal Network, the Orellana's Network
- 6 Comparison and Discussion
- 7 Conclusions, Limitations and Future Work
- References
- Analysis of the Web Graph Aggregated by Host and Pay-Level Domain
- 1 Introduction
- 2 Related Work
- 3 Datasets and Definitions
- 4 Methodology of Analysis
- 5 Analysis of the PLD Graph
- 5.1 Degree Distributions
- 5.2 Components
- 5.3 Distances and Diameters
- 6 Analysis of the Host Graph
- 7 Conclusion
- References
- Characterizing Temporal Bipartite Networks - Sequential- Versus Cross-Tasking
- 1 Introduction
- 2 Real-World Temporal Bipartite Networks
- 2.1 Dataset Description
- 2.2 Network Representation
- 2.3 Basic Network Characteristics
- 3 Quantifying the Sequential/Cross-Tasking Level
- 3.1 Relative Switch Frequency
- 3.2 Relative Distraction in Time
- 3.3 Comparison of Two Real-World Networks
- 4 Correlation Between Sequential/Cross-Tasking Level and Other Centrality Metrics
- 5 Conclusion
- References
- A General Powerful Graph Pattern Matching System for Data Analysis
- 1 Introduction
- 2 Problem Formulation and Method
- 3 Applications and Experimental Analysis
- 3.1 Highly Collaborative Groups of Researchers
- 3.2 Design Pattern Observer
- 3.3 Change Coupling
- 4 Conclusion
- References
- Spectral Measures of Distortion for Change Detection in Dynamic Graphs
- 1 Introduction
- 1.1 Related Work
- 2 Proposed Framework
- 2.1 Distortion Energies
- 2.2 Choice of Scale via Reduced Functional Space
- 2.3 An Algorithm to Compute the Spectral Distortion
- 3 Experimental Evaluation
- 3.1 Experimental Comparison and Discussion
- 4 Conclusion, Limitations and Future Work
- References
- Rich-Clubs in Preferential Attachment Networks
- 1 Introduction
- 1.1 Background
- 1.2 The G(p) Model
- 1.3 Rich Clubs
- 1.4 Related Work
- 1.5 Contributions
- 2 Technical Preliminaries
- 3 Known Bounds
- 4 Proofs of the Main Theorems
- 5 Discussion
- References
- The Impact of Indirect Connections: The Case of Food Security Problem
- Abstract
- 1 Introduction
- 2 Edge Importance Measures
- 3 The Case of Food Export/Import Network
- 4 Conclusion
- Acknowledgments
- Reference
- A Compressive Sensing Framework for Distributed Detection of High Closeness Centrality Nodes in Networks
- 1 Introduction
- 2 Preliminaries
- 2.1 Compressive Sensing/Sampling
- 2.2 Compressive Sensing over Graphs
- 3 Related Work
- 3.1 Local Closeness Metrics
- 3.2 CS-Based Methods for Data Aggregation
- 4 Proposed Method
- 4.1 Proposed Local Metric
- 4.2 Measurement Construction and Score Aggregation
- 4.3 Complexity Analysis
- 5 Experimental Evaluation
- 5.1 Datasets
- 5.2 Settings
- 5.3 Evaluation Results
- 6 Conclusion
- References
- Machine Learning and Networks
- Bringing a Feature Selection Metric from Machine Learning to Complex Networks
- 1 Introduction
- 2 Feature and Node F-Measure
- 3 Node F-Measure Applied to Artificial Networks
- 3.1 LFR Networks
- 3.2 Correlation with Centrality Measures
- 3.3 Correlation with Community Role Measures
- 4 Node F-Measure Applied to Real Networks
- 5 Conclusion and Perspectives
- References
- Multi-Net: A Scalable Multiplex Network Embedding Framework
- 1 Introduction
- 2 Related Work
- 3 Problem Formulation
- 4 Methodology
- 4.1 Learning Objective
- 4.2 Random Walks on Multiplex Network
- 5 Experiments and Results
- 5.1 Experimental Setup
- 5.2 Experiment Results
- 5.3 Evaluation on Algorithm Scalability
- 6 Discussion and Future Work
- References
- Learning Structural Node Representations on Directed Graphs
- 1 Introduction
- 2 Related Work
- 3 Preliminaries
- 4 Learning Structural Node Embeddings on Directed, Weighted Graphs
- 5 Experimental Evaluation
- 6 Conclusion
- References
- Automatic Identification of Component Roles in Software Design Networks
- 1 Introduction
- 2 Preliminaries
- 2.1 Class Diagrams
- 2.2 Network Construction
- 2.3 Network Concepts
- 2.4 Class Roles
- 3 Related Work
- 4 Approach
- 4.1 Semantic and Network Features
- 4.2 Machine Learning Model
- 5 Data
- 6 Results
- 7 Conclusion
- References
- Exploring Partially Observed Networks with Nonparametric Bandits
- 1 Introduction
- 2 Related Work
- 3 Proposed Bandit Based Probing Algorithm
- 3.1 Problem Definition
- 3.2 Calculation of Expected Reward of Candidate Nodes
- 3.3 Bandit Algorithm
- 4 Experiments
- 4.1 Data
- 4.2 Impact of Initial Sampling Algorithm
- 4.3 Algorithms
- 5 Results
- 5.1 Analysis on Synthetic Networks
- 5.2 Results on Real-World Networks
- 6 Conclusions
- References
- Explicit Feedbacks Meet with Implicit Feedbacks: A Combined Approach for Recommendation System
- 1 Introduction
- 2 Methodology
- 3 Experiments
- 4 Conclusion and Future Work
- References
- Quantum Walk Neural Networks for Graph-Structured Data
- 1 Introduction
- 2 Graph Quantum Walks
- 3 Quantum Walk Neural Networks
- 3.1 Edge Ordering
- 4 Experiments
- 4.1 Node Regression
- 4.2 Graph Classification
- 4.3 Graph Regression
- 5 Limitations
- 6 Concluding Remarks
- References
- Modeling Human Behavior
- Advertisement Allocation and Mechanism Design in Native Stream Advertising
- 1 Introduction
- 1.1 Our Contribution
- 1.2 Related Work
- 2 Native Advertising Meets Interval Scheduling
- 2.1 Hardness of Native Advertising
- 2.2 Algorithms for Native Stream Advertising
- 3 Truthful Native Advertising Mechanisms
- 3.1 Preliminaries
- 3.2 Truthfulness in Expectation
- 3.3 Deterministic Truthfulness
- 4 Conclusions
- References
- Let's Talk About Refugees: Network Effects Drive Contributor Attention to Wikipedia Articles About Migration-Related Topics
- 1 Introduction
- 1.1 Background and Further Related Work
- 2 Relational Event Models for the Wikipedia Network
- 2.1 Data
- 2.2 The Network of Past Events
- 2.3 A Framework for Modeling Dyadic, Typed Events
- 2.4 Parameter Estimation Under Sampling
- 2.5 Explanatory Variables (Statistics)
- 3 Results and Discussion
- 4 Conclusion
- References
- Understanding Behavioral Patterns in Truck Co-driving Networks
- 1 Introduction
- 2 Related Work
- 3 Network Construction
- 3.1 Truck Observation Data
- 3.2 Construction from Raw Data
- 3.3 Co-driving Network
- 3.4 Robustness Checks
- 3.5 Regional Co-driving Network
- 4 Approach
- 4.1 Network-Driven Understanding of Co-driving Behavior
- 4.2 Community-Driven Understanding of Co-driving Behavior
- 5 Results
- 5.1 Network Statistics
- 5.2 Attribute Assortativity
- 5.3 Average Maximal Community Assortativity
- 6 Conclusion
- References
- Theoretical Study of Self-organized Phase Transitions in Microblogging Social Networks
- Abstract
- 1 Introduction
- 2 Brief Theoretical Background
- 3 Three-Parameter Kinetics of the Phase Transitions
- 3.1 Self-organized Scheme
- 3.2 Kinetics of the Phase Transition
- 3.3 Stochastic Behavior of the Phase Transitions
- 4 Conclusions
- Acknowledgments
- References
- Using Active Queries to Learn Local Stochastic Behaviors in Social Networks
- 1 Introduction
- 2 Preliminaries
- 3 Inferring Probabilistic Threshold Functions
- 4 Experimental Evaluation of Our Algorithm
- 5 Future Research Directions
- References
- Networking Strategies and Efficiency in Human Communication Networks
- 1 Introduction
- 2 Developing Models of Networking Strategies
- 2.1 Structural Change Strategy
- 2.2 Frequency Change Strategy
- 3 Measuring Efficiency
- 4 Data
- 5 Results
- 5.1 Efficiency under Complementary Networking Strategies
- 5.2 Comparison with an Empirical Reconstruction of the Networking Process
- 6 Discussion
- References
- Influence, Reputation and Trust
- The Costs of Overambitious Seeding of Social Products
- 1 Introduction
- 2 The Model, the Networks, and the Simulations
- 3 Simulation Results and the Costs of Overambitious Seeding
- 3.1 Synthetic Networks
- 3.2 Simulations: Facebook Friendship Graphs
- 4 Conclusion
- References
- Procedural Influence on Consensus Formation in Social Networks
- 1 Introduction
- 2 Procedural Influence
- 3 Modelling Procedural Influence
- 3.1 A Multidimensional Model of Social Influence
- 3.2 Integrating Procedural Influence
- 4 Agent-Based Simulation
- 4.1 Model Setup and Experiment Design
- 4.2 Sensitivity Analysis
- 5 Conclusion
- References
- Peer Influence in Large Dynamic Network: Quasi-experimental Evidence from Scratch
- 1 Introduction
- 2 Methods
- 3 Results
- 3.1 Production Behaviour
- 3.2 Consumption Behaviour
- 4 Discussion
- A Appendix
- References
- Modeling the Co-evolving Polarization of Opinion and News Propagation Structure in Social Media
- 1 Introduction
- 2 Opinion Polarization Models
- 3 Model Description
- 4 Results and Discussion
- 4.1 Effects of News Polarization
- 4.2 Interaction Structure of Polarized Network
- 4.3 Effects of The Model Parameters
- 5 Conclusion
- References
- Community-Based Measures for Social Capital
- 1 Introduction
- 2 Related Work
- 3 Community-Based Social Capital Measures
- 3.1 Social Network Model
- 3.2 Community Detection
- 3.3 Similarity and Diversity
- 3.4 Bonding and Bridging Social Capital
- 4 Experiments
- 4.1 Implementation
- 4.2 Results
- 5 Conclusions
- References
- Social Networks
- Relating an Adaptive Social Network's Structure to Its Emerging Behaviour Based on Homophily
- Abstract
- 1 Introduction
- 2 Network-Oriented Modeling by Temporal-Causal Networks
- 3 Adaptive Networks Based on Homophily
- 4 Example Simulations
- 5 Relevant Properties of Homophily Combination Functions
- 6 Relating Adaptive Network Structure to Bonding Behaviour
- 7 Discussion
- References
- A Socio-Temporal Hashtag Recommendation System for Twitter
- 1 Introduction
- 1.1 Related Works
- 1.2 Motivation and Our Contributions
- 2 Central Idea
- 2.1 Temporal Burst Modeling
- 2.2 Socio-Temporal Modeling
- 2.3 Combining and Re-ranking
- 3 Experiments
- 3.1 Dataset Description
- 3.2 Performance Metrics
- 3.3 Recommendation of Top-M Hashtags by System
- 3.4 Recommendation of Exact Number of Hashtags by System
- 3.5 Comparing with The Literature
- 4 Conclusion
- References
- Assessing Topical Homophily on Twitter
- 1 Introduction
- 1.1 Background and Motivation
- 1.2 Our Contributions
- 2 Our Approach
- 2.1 Identifying Topics as Hashtag Clusters
- 2.2 User Participation in Topic Clusters
- 2.3 User Pair Similarities
- 2.4 Correlating Similarity with Familiarity
- 3 Experiments
- 3.1 Dataset Description
- 3.2 Results
- 4 Conclusion
- References
- Network Topology and Tie Strength in Online Communities of Practice
- Abstract
- 1 Introduction
- 2 Theoretical Background
- 3 Hypothesis Development
- 4 Methods
- 4.1 Research Context
- 4.2 Empirical Model
- 4.3 Data and Variables
- 5 Results
- 6 Robustness Tests
- 7 Conclusion
- References
- Survey on Social Ego-Community Detection
- 1 Introduction
- 2 Related Work
- 2.1 Quality Function Optimization
- 2.2 Triangles-Based Approach
- 2.3 Similarity Measures
- 3 Strengths and Weaknesses of Existing Works
- 4 Ego-Community Detection Challenges
- 4.1 Challenge 1: Hierarchical Ego-Community Detection
- 4.2 Challenge 2: Dynamic Ego-Community Tracking
- 4.3 Challenge 3: Validation of Dynamic Algorithms
- 4.4 Challenge 4: Multidimensional Analysis
- 5 Conclusion
- References
- Diversity, Homophily and the Risk of Node Re-identification in Labeled Social Graphs
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 4 Datasets
- 4.1 Real Network Datasets
- 4.2 Synthetic Graphs
- 5 Empirical Results
- 5.1 The Vulnerability Cost of Node Attributes
- 5.2 Diversity Matters, Homophily Not
- 6 Summary and Discussions
- References
- Characterizing Key Players in Child Exploitation Networks on the Dark Net
- 1 Introduction
- 2 Preliminaries
- 2.1 Two-Mode Networks
- 2.2 One-Mode Networks
- 3 Related Work
- 4 Data
- 4.1 Forum Data
- 4.2 Domain-Specific Node Metadata
- 5 Approach
- 5.1 Determining the Right Projection Method
- 5.2 Key User Characterization
- 6 Results
- 6.1 Network Characteristics
- 6.2 Comparing Projections
- 6.3 Identifying Key Players
- 6.4 User Roles
- 7 Conclusion and Future Work
- References
- Bots in Nets: Empirical Comparative Analysis of Bot Evidence in Social Networks
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Data
- 3.2 Bot Enrichment
- 3.3 Construct Retweet Network
- 3.4 Analyze Data
- 4 Results and Discussion
- 4.1 Bot and Human Participation Rates
- 4.2 In-Group and Cross-Group Communications
- 4.3 Centrality Analysis
- 4.4 Community Detection
- 5 Conclusion and Future Work
- Acknowledgments
- References
- Detecting Potential Cyber Armies of Election Campaigns Based on Behavioral Analysis
- 1 Introduction
- 2 Related Works
- 3 Methodology
- 4 Result
- 4.1 Candidate Popularity
- 4.2 Commenters Polarity
- 4.3 Commenters Response Time
- 5 Conclusion
- References
- Social Stratification from Networks of Leveling Ties
- 1 Introduction
- 2 Networks of Leveling Ties
- 2.1 Empirical Networks
- 2.2 Idealized Networks
- 3 Measures of Intervality
- 4 Centrality Indices
- 5 Application
- 5.1 Cambridge Social Interaction and Stratification Scale
- 5.2 Leveling Ties Between Occupations
- 6 Discussion
- References
- Quantifying the Strength of the Friendship Paradox
- 1 Introduction
- 2 Preliminaries
- 2.1 Friendship Index
- 2.2 Global and Local Assortativity - Quantifying Homophily
- 2.3 Results for Special Graphs
- 3 Theoretical Results on Friendship Index
- 3.1 A Lower Bound on Global Measures of FI
- 3.2 Erdos-Renyi Graphs
- 4 Experimental Results
- 4.1 Network Models
- 4.2 Real World Networks
- 5 Concluding Remarks
- References
- Social Media Group Structure and Its Goals: Building an Order
- 1 Introduction
- 2 Literature Study
- 3 Method
- 4 Data and Preprocessing
- 5 Results
- 5.1 Openness to Friends
- 5.2 Social Temperature
- 6 Discussion
- 7 Conclusion
- References
- Networks in Finance and Economics
- Complex Interbank Network Estimation: Sparsity-Clustering Threshold
- 1 Introduction
- 2 Related Literature
- 3 Methodology
- 3.1 Characteristic Network Structure
- 3.2 Properties of the Characteristic Network Structure
- 4 Empirical Results
- 5 Discussion
- References
- Clearing Algorithms and Network Centrality
- 1 Introduction
- 2 Clearing Model
- 3 Network Centrality
- 4 Conclusion
- References
- Inferring Short-Term Volatility Indicators from the Bitcoin Blockchain
- 1 Introduction
- 2 Data and Methods
- 2.1 Low-Dimensional Representations of Transaction Graphs
- 2.2 Early Warning Indicator (EWI)
- 2.3 Inference Step
- 3 Results
- 3.1 Extreme Event Definition
- 3.2 Evaluation
- 3.3 Statistical and Sensitivity Analysis for EWI
- 4 Discussion and Conclusion
- A Appendix
- References
- Analysis of News Flow Dynamics Based on the Company Co-mention Network Characteristics
- 1 Introduction
- 2 Links, Degree Distribution and Local Clustering Coefficient
- 3 Company Co-mention Network Evolution
- 3.1 News Analytics Data
- 3.2 Company Co-mention Network
- 3.3 Degree and the Clustering-Degree Distributions
- 3.4 The Evolution of the Size of Maximum Cliques
- 4 Conclusion
- References
- Capturing Financial Volatility Through Simple Network Measures
- 1 Introduction
- 2 Methods: Using Node Degree and Motifs to Analyze Financial Networks
- 2.1 Financial Markets Structure
- 3 Results and Discussion
- 4 Conclusions and Future Work
- References
- The Graph Structure of Bitcoin
- 1 Introduction
- 2 Background and Related Work
- 3 Formal Definitions and Method
- 4 The Bow Tie Structure of the Bitcoin Users Graph
- 4.1 Evaluation of Components Metrics
- 5 Temporal Analysis
- 6 Conclusions
- References
- Emergent Relational Structures at a ``Sharing Economy'' Festival
- 1 Introduction
- 2 Multi-level Network Structures
- 3 Empirical Setting and Data
- 4 Variables and Measures
- 4.1 Thematic Affinity
- 4.2 Status
- 4.3 Positional Similarity
- 4.4 Reciprocity
- 4.5 Controls
- 5 Exponential Random Graph Model of the Attendance Network
- 5.1 Results
- 6 Discussion and Conclusions
- 6.1 Thematic Affinity Confers Self-deference
- 6.2 Preference for Novelty over Status
- 6.3 Popularity Produces Conformity
- 6.4 Unreciprocated Ties in Competition
- References
- Biological Networks
- Comparison of BiClusO with Five Different Biclustering Algorithms Using Biological and Synthetic Data
- 1 Introduction
- 2 Reference Biclustering Methods
- 3 Method of BiClusO
- 4 Selection of Dataset
- 4.1 Biological Data
- 4.2 Synthetic Data
- 5 Score Calculation for Biological data
- 6 Score Calculation for Synthetic Data
- 7 Parameter Setting
- 8 Results
- 8.1 Biclusters Based on Biological Data
- 8.2 Comparison Based on Synthetic Data
- 9 Conclusion
- References
- Phase Transitions in Spatial Networks as a Model of Cellular Symbiosis
- 1 Introduction and Motivation
- 1.1 Background
- 2 The Spatio-Temporal Model
- 2.1 Design of the Spatio-Temporal Network Model
- 2.2 Introducing Distance Functions
- 3 Critical Behavior and Phase Transitions
- 4 Simulation and Analysis
- 5 Conclusion and Future Directions
- References
- Exploiting Complex Protein Domain Networks for Protein Function Annotation
- 1 Introduction
- 2 Methods
- 2.1 Protein-Protein Network Construction
- 2.2 Label Propagation for Protein Function Annotation
- 3 Experiments
- 3.1 Evaluation Metrics
- 3.2 GrAPFI Performance Analysis
- 4 Conclusion
- References
- Multi-omic Network Regression: Methodology, Tool and Case Study
- 1 Introduction
- 2 Background
- 2.1 Metabolic Modelling
- 2.2 Cox Regression
- 3 Theory and Computational Methods
- 3.1 Network Regression
- 3.2 Network Reduction
- 3.3 Implementation Outline
- 4 Results and Discussion
- 4.1 Data Generation
- 4.2 Loopless FBA
- 4.3 Pareto Reconstruction
- 5 Conclusions
- A Code Guide
- References
- Network Neuroscience
- Functional Connectivity Hubs and Thalamic Hemodynamics in Rolandic Epilepsy
- Abstract
- 1 Introduction
- 2 Methods
- 2.1 Participants
- 2.2 MRI Data Acquisition
- 2.3 Preprocessing
- 2.4 HRF Signature Extraction and Blind Deconvolution for Resting State fMRI
- 2.5 Functional Connectivity Density Mapping (FCD)
- 2.6 Statistics
- 3 Results
- 4 Discussion
- Acknowledgments
- References
- Comparison of Brain Connectivity Networks Using Local Structure Analysis
- 1 Fixed-Period Problems: The Sublinear Case
- 2 Method
- 2.1 Data Model
- 2.2 Distance Between Coherence Networks
- 3 Performance
- 3.1 Comparison with the Inexact Graph Matching Method
- 3.2 Real Brain Connectivity Results
- 4 Conclusions and Future Work
- References
- Age Related Topological Analysis of Synchronization-Based Functional Connectivity
- 1 Introduction
- 2 Materials
- 2.1 Participants
- 2.2 fMRI Acquisition and Preprocessing
- 3 Methods
- 3.1 Synchronization-Based Functional Connectivity
- 3.2 Topological Analysis
- 3.3 Regression Analysis
- 4 Results
- 4.1 Phase Space Parameters
- 4.2 Global Graph Metrics
- 4.3 Local Graph Metrics
- 5 Discussion and Conclusion
- References
- Using Algorithmic Complexity to Differentiate Cognitive States in fMRI
- 1 Introduction
- 2 Data Acquisition and Processing
- 3 Estimating Algorithmic Complexity
- 4 Experimental Setup and Results
- 5 Conclusions and Future Research
- References
- Author Index
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