Complex Networks and Their Applications VIII

Name: Complex Networks and Their Applications VIII | Volume 1 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019
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Volume 1 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019

Hocine Cherifi Sabrina Gaito José Fernendo Mendes Esteban Moro Luis Mateus Rocha(Editor)

Springer (Publisher)

Published on 25. November 2019

XXVII, 979 pages

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Content

Intro
Preface
Organization and Committees
General Chairs
Advisory Board
Program Chairs
Program Co-chairs
Satellite Chairs
Lightning Chairs
Poster Chairs
Publicity Chairs
Tutorial Chair
Sponsor Chair
Social Media Chair
Local Committee Chair
Local Committee
Publication Chair
Submission Chair
Web Chair
Program Committee
Contents
Link Analysis and Ranking
LinkAUC: Unsupervised Evaluation of Multiple Network Node Ranks Using Link Prediction
1 Introduction
2 LinkAUC
2.1 Link Ranks
2.2 Link Rank Evaluation Using AUC
2.3 Relation to Rank Density
3 Experiments
3.1 Networks
3.2 Ranking Algorithms
3.3 Measures
3.4 Results
4 Conclusions and Future Work
References
A Gradient Estimate for PageRank
1 Introduction/Background
2 Preliminaries
2.1 Spectral Graph Theory and Graph Laplacians
2.2 PageRank
2.3 Graph Curvature
3 Gradient Estimate for PageRank
4 Harnack-Type Inequality
5 Conclusions, Applications, and Future Work
References
A Persistent Homology Perspective to the Link Prediction Problem
1 Introduction
2 Persistent Homology of a Graph
2.1 Persistence Diagram of a Graph
3 Link Prediction via Persistent Homology
3.1 Why This Algorithm Works?
4 Experiments
4.1 Experimental Protocol
4.2 Results and Discussions
5 Conclusions and Future Work
References
The Role of Network Size for the Robustness of Centrality Measures
1 Introduction
2 Methods
3 Experiments with Empirical Networks
4 Experiments with Random Graphs
5 Conclusions and Final Remarks
References
Novel Edge and Density Metrics for Link Cohesion
1 Introduction
2 Link Cohesion Calculation
3 Using Link Cohesion
3.1 Link Cohesion Density and Pruning Algorithm
3.2 Other Potential Uses of Link Cohesion
4 Relevant Literature
5 Results
5.1 Experimental Datasets
5.2 Edge Pruning Study
5.3 Edge Weights Study: Correlations with Edge Betweenness
6 Conclusion
References
Facility Location Problem on Network Based on Group Centrality Measure Considering Cooperation and Competition
1 Introduction
2 Related Work
2.1 Centrality Analysis of Spatial Networks
2.2 Facility-Location Problem in Networks
3 Problem Setting
4 Proposed Measure
5 Experiments
5.1 Dataset
5.2 Measures Used for Comparison
5.3 Comparison of Candidate Locations for New Stores
5.4 Analysis of Competition Structure
6 Conclusion
References
Finding Dominant Nodes Using Graphlets
1 Introduction
2 Graphlet Dominance
3 Comparison with Node Centrality Measures
4 Ranking of Scientific Authors
4.1 Motivation
4.2 Network Description
4.3 Results
5 Conclusions
References
Sampling on Networks: Estimating Eigenvector Centrality on Incomplete Networks
1 Introduction
2 The Problem
2.1 A Theoretically Motivated Sampling Method
2.2 An Extension of the Sampling Algorithm
3 Empirical Studies
3.1 Results on Synthetic and Real Data
4 Conclusions
References
Community Structure
Repel Communities and Multipartite Networks
1 Introduction
2 Related Work
3 Background and Definitions
3.1 Networks
3.2 Applications
4 Algorithms
4.1 Use of the Graph Complement
4.2 Finding Repel Communities
5 Experiments
5.1 Datasets
5.2 Effectiveness of the Algorithms
5.3 Algorithm Comparison
5.4 Similarity of Discovered Repel Communities
5.5 Comparison with Ground Truth Communities
6 Conclusion
References
The Densest k Subgraph Problem in b-Outerplanar Graphs
1 Introduction
2 An Algorithm to Find the Densest k Subgraph Problem in Outerplanar Graphs
3 An Algorithm to Find the Densest k Subgraph Problem in b-Outerplanar Graphs
4 Polynomial Time Approximation Scheme and Future Work
A Pseudocode Selections
References
Spread Sampling and Its Applications on Graphs
1 Introduction
2 Related Work
3 Methology
3.1 Designing Spread Sampling
3.2 High Community Diversity
3.3 Complexity Analysis
3.4 Impact of Sampling Parameters
4 Applications of Spread Sampling
4.1 Overlapping Community Detection Seeding
4.2 Network A/B Testing
5 Conclusions
References
Eva: Attribute-Aware Network Segmentation
1 Introduction
2 The Eva Algorithm
3 Experiments
4 Related Work
5 Conclusion
References
Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery
1 Introduction
2 Angel
3 Evaluation
3.1 Experimental Results
4 Related Works
5 Conclusion
References
Metrics Matter in Community Detection
1 Introduction
2 Community Detection
3 Preliminaries
3.1 Partition Structures
3.2 Random Models
3.3 Information Theory
4 What We've Been Doing Wrong
5 Recipe for Proper Evaluation
6 Relationships Between Measures
7 Setting a Trap: Leximin, an Adversarial Method
8 Springing the Trap: Experiment
9 Postmortem of a Trapped Measure: Discussion and Results
10 Related Work
11 Conclusion and Future Work
References
An Exact No Free Lunch Theorem for Community Detection
1 Introduction
2 Background
2.1 Community Detection
2.2 No Free Lunch Theorems
2.3 Community Detection as Supervised Learning
2.4 Loss Functions and a Priori Superiority
3 Previous Result: Approximate No Free Lunch Theorem
4 Diagnosis: Random Models
5 An Exact No Free Lunch Theorem
5.1 Generalizer-Independence of `3´9`42`"?613A``45`47`"603AAMIall1
5.2 Other Measures
6 Conclusion
References
Impact of Network Topology on Efficiency of Proximity Measures for Community Detection
1 Introduction
2 Related Work
3 Background and Preliminaries
3.1 Definitions
3.2 Clustering Methods
3.3 Measures
3.4 Network Generation
3.5 Clustering Quality Evaluation
4 Experimental Methodology
5 Results
6 Conclusion
References
Identifying, Ranking and Tracking Community Leaders in Evolving Social Networks
1 Introduction
2 Related Methods and Techniques
3 Identifying, Ranking and Tracking Community Leaders
3.1 Dynamic Community Detection
3.2 Dynamic Laplacian Centrality
3.3 Combining Centrality and Dynamic Community Detection
4 Results
5 Conclusions
References
Change Point Detection in a Dynamic Stochastic Blockmodel
1 Introduction
2 Graph Models
2.1 The Dynamic Stochastic Blockmodel
3 The Resistance Perturbation Distance
4 Main Result
5 Experiments
6 Discussion
References
A General Method for Detecting Community Structures in Complex Networks
Abstract
1 Introduction
2 Community Detection Method
3 Example Network Models
4 Detected Communities and Their Sub-structures
4.1 Zachary's Karate Club
4.2 Lusseau's Bottlenose Dolphin Network
5 Conclusions
References
A New Metric for Package Cohesion Measurement Based on Complex Network
1 Introduction
2 Preliminary
2.1 Basis of Attributes of Community
2.2 Class Dependency Graph
3 Cohesion Metrics Based on Complex Network
3.1 Cohesion Metrics
3.2 Theoretical Verification of Our Cohesion Metric
3.3 Refactoring Algorithm
4 Experiment and Analysis
4.1 Refactoring and Analysis
4.2 Randomly Disturb and Recover
5 Conclusion
References
A Generalized Framework for Detecting Social Network Communities by the Scanning Method
1 Introduction
2 The Standard Framework of Scan Statistics
3 The Generalized Likelihood-Based Framework
3.1 Random Connection Probability Model
3.2 Logit Model
4 Simulation Study and Comparison
4.1 Type I Error
4.2 Testing Power
4.3 Comparisons of Detection Accuracy
5 Discussion and Conclusion
References
Comparing the Community Structure Identified by Overlapping Methods
1 Introduction
2 Methods for Overlapping Community Detection
3 Experiments and Discussion
3.1 Quality Measures
3.2 Node Membership
3.3 Community Size
3.4 Overlapping Size
3.5 Edge Probability on the Overlapping Region
4 Conclusions and Future Directions
References
Semantic Frame Induction as a Community Detection Problem
1 Introduction
2 Related Work
3 Semantic Frame Induction Approach
4 Experimental Setup
4.1 Dataset
4.2 Evaluation Approach
4.3 Implementation Details
5 Results and Discussion
6 Conclusions
References
A New Measure of Modularity in Hypergraphs: Theoretical Insights and Implications for Effective Clustering
1 Introduction
2 Background
2.1 Hypergraphs
2.2 Modularity
3 Hypergraph Modularity
4 Iterative Hyperedge Reweighting
4.1 A Simple Example
5 Evaluation on Ground Truth
5.1 Compared Methods
5.2 Datasets
5.3 Experiments
5.4 Results
5.5 Effect of Reweighting on Hyperedge Cuts
6 Conclusion
References
Diffusion and Epidemics
Crying ``Wolf'' in a Network Structure: The Influence of Node-Generated Signals
1 Introduction
2 Related Work
3 Useful Definitions
4 Model
5 Example: Facebook Sample Graph
6 Methods
6.1 Preparation of Networks
6.2 Numerical Simulations
6.3 Analysis: Decision Trees
7 Results
8 Conclusions
References
Vaccination Strategies on a Robust Contact Network
1 Introduction
2 Related Works
3 The Network
4 Graph Representation
5 Simulation Model
6 Vaccination Strategies
7 Results
8 Conclusion
References
Total Positive Influence Domination on Weighted Networks
1 Introduction
2 Preliminaries
2.1 Previous Work
3 Greedy Algorithms
4 An Algorithm Using Community Structure - RRWC
5 Results
5.1 Real-Life Networks
5.2 Random Networks
5.3 Comparison
6 Conclusions
References
Modelling Spatial Information Diffusion
Abstract
1 Introduction
2 Related Work
3 Data and Methods
3.1 Twitter Data
3.2 Model Design
4 Effect of the Distance Decay
5 Conclusions
Acknowledgements
References
Rejection-Based Simulation of Non-Markovian Agents on Complex Networks
1 Introduction
2 Multi-agent Model
2.1 Semantics
3 Previous Simulation Approaches
3.1 Non-Markovian Gillespie Algorithm
3.2 Laplace-Gillespie Algorithm
4 Our Method
4.1 Rate Over-Approximation
4.2 The RED-Sim Algorithm
5 Case Studies
6 Conclusions
References
Community-Aware Content Diffusion: Embeddednes and Permeability
1 Introduction
2 Community-Aware Diffusive Modeling
3 Experimental Analysis
4 Related Works
5 Conclusion
References
Can WhatsApp Counter Misinformation by Limiting Message Forwarding?
1 Introduction
2 Related Work
3 Datasets
4 Spreading Coverage and Dynamics
5 Network Structure
6 Impact of Forwarding Limitations on Information Spread
7 Conclusions
References
Modeling Airport Congestion Contagion by SIS Epidemic Spreading on Airline Networks
1 Introduction
2 Traffic Vulnerability of an Airport
2.1 Data
2.2 Definition and Statistical Properties
3 SIS Model on Airline Transportation Networks
3.1 Network Construction
3.2 Individual-Based Mean-Field Approximation of SIS Model
4 Results and Discussion
4.1 Network Characteristics
4.2 Model Evaluation via Vulnerability Distribution
4.3 Model Evaluation via Airport Ranking in Vulnerability Distribution
5 Model Generalization
6 Conclusion
References
A Population Dynamics Approach to Viral Marketing
1 Introduction
2 Marketing Referral Programs and Growth Hacking Marketing
3 Methods: An Agent-Based Marketing Referral Model
4 Results and Discussion
4.1 Social Propagation and Population Dynamics
4.2 The Influence of Service Cost Structure
4.3 Network Impact on Propagation and Profitability
5 Conclusions and Final Remarks
References
Integrating Environmental Temperature Conditions into the SIR Model for Vector-Borne Diseases
1 Introduction
2 Related Work
2.1 Environmental Factors of Vector-Borne Epidemic Spreading
2.2 Contact Network of the Host Population
3 Description of the Model
4 Mathematical Formulation
5 Simulation of the Model and Results Analysis
6 Conclusion and Future Work
References
Opinion Diffusion in Competitive Environments: Relating Coverage and Speed of Diffusion
1 Introduction
2 A Formal Framework for Competitive Diffusion
3 Experimental Evaluation
3.1 Speed and Coverage
3.2 Speed and Consensus
4 Conclusion
References
Beyond Fact-Checking: Network Analysis Tools for Monitoring Disinformation in Social Media
1 Introduction
2 Related Work
3 The Toolbox
4 Politics and Information in 2016 Italy
4.1 Disinformation Stories
5 Findings
5.1 Disinformation Prevalence
5.2 Polarization and Disinformation
5.3 Interaction Graphs and Disinformation
6 Conclusion
References
Suppressing Information Diffusion via Link Blocking in Temporal Networks
1 Introduction
2 Methods
2.1 Representation of Temporal Networks
2.2 Information Diffusion Backbone
2.3 Link Centrality Metrics
2.4 Link Blocking and Evaluation
3 Data Description
4 Empirical Results
5 Conclusion
References
Using Connected Accounts to Enhance Information Spread in Social Networks
Abstract
1 Introduction
2 Model
2.1 Creation of Spreading Groups in the Network
2.2 Four Seeding Strategies
2.3 Temporal Examination of Seeding and Spread
2.4 Modeling the Retention Loss
2.5 Simulation Scheme
3 Results
3.1 Spreading by Spread Groups vs. Other Strategies
3.2 Simulations Fit to Real Spreading Patterns and Additional Examinations
4 Conclusion
Acknowledgement
References
Designing Robust Interventions to Control Epidemic Outbreaks
1 Introduction
2 Notation and Problems
3 Our Approach
3.1 Algorithm mmRound for Deterministic Sources and Single Stage
3.2 Extension to Two Stage
3.3 Extension to Probabilistic Sources and p&1
4 Experiments
4.1 Dataset and Methods
4.2 Properties of Min-Max Objective
4.3 Impact of T and B0/BT
4.4 Characteristics of Nodes Picked for Intervention
5 Related Work
6 Conclusions
References
Dynamics on/of Networks
The Impact of Network Degree Correlation on Parrondo's Paradox
Abstract
1 Introduction
2 Model
3 Method
4 Simulation Results
4.1 The Effect of Network Degree Correlation on Parrondo's Paradox Under Cooperative and Competitive Behaviors
4.2 Microcosmic Mechanism Analysis of the Paradox
4.2.1 The Cooperative Pattern P1 = 0.695, P2 = 0.28
4.2.2 The Competitive Pattern: p1 = 0.175, p2 = 0.85
5 Conclusions
Acknowledgments
References
Analysis of Diversity and Dynamics in Co-evolution of Cooperation in Social Networking Services
1 Introduction
2 Modeling Social Networking Services
2.1 Agents
2.2 SNS-Norms Game
2.3 Structure of Network
3 Co-evolutionary Game
3.1 Multiple-World GA
3.2 Genetic Operations
4 Experiments and Discussion
4.1 Comparison of Learned Strategies and Fitness Values
4.2 Distribution of Strategies and Dynamics of Learning Process
4.3 Discussion
5 Conclusion
References
Shannon Entropy in Time-Varying Clique Networks
Abstract
1 Introduction
2 Background
2.1 Information Entropy
2.2 Time Varying Graphs
2.3 Clique Networks
3 Materials and Method
3.1 Dataset
3.2 Construction of Time-Varying Semantic Networks of Titles of Scientific Papers
3.3 Sliding Window
3.4 Metrics Used
3.5 Information Entropy in Titles Networks
3.6 Limits for Entropy Value
4 Results and Discussion
5 Conclusions
Acknowledgment
References
Two-Mode Threshold Graph Dynamical Systems for Modeling Evacuation Decision-Making During Disaster Events
1 Introduction
2 Evacuation Decision-Making Model
2.1 Motivation from Social Science
2.2 A Graph Dynamical Systems Framework
3 Analyzing Dynamical Properties in Different Network Models
4 Agent-Based Simulations and Results
5 Related Work
6 Summary and Conclusions
References
Spectral Evolution of Twitter Mention Networks
1 Introduction
2 Data Description
3 Spectral Evolution Model
3.1 Spectral Evolution Model Verification
3.2 Growth Models
4 Case Study: Twitter Conversations
5 Conclusions
References
Network Models
Minimum Entropy Stochastic Block Models Neglect Edge Distribution Heterogeneity
1 Entropy Based Stochastic Block Model Selection
2 The Issue with Heavily Populated Graph Regions
3 The Density Threshold
4 Consequences on Model Selection
5 Discussion
References
Three-Parameter Kinetics of Self-organized Criticality on Twitter
Abstract
1 Introduction
2 One of the Possible Mechanisms of Twitter Self-organizing Transition in a Critical State
3 The Formalism
4 Discussion
5 Conclusion
References
Multi-parameters Model Selection for Network Inference
1 Introduction
2 Network Inference
3 Likelihood Scores for Multi-parameters Model Selection
4 Stability Based Multi-parameters Model Selection
5 Experiments and Results
6 Conclusion
References
Scott: A Method for Representing Graphs as Rooted Trees for Graph Canonization
1 Problem Statement and Related Works
1.1 Canonical Form of a Graph
1.2 Existing Canonization Algorithms
1.3 Proposed Algorithm (SCOTT)
2 Canonical Notation of Rooted Trees
2.1 Definitions and Properties
2.2 Ordering on the Set of Labelled Trees
3 Proposition: Scott Algorithm
3.1 Steps Summary
3.2 Time Complexity
4 Application
4.1 Shrunken Multipedes Graphs
4.2 Molecular Graphs
5 Discussion and Conclusion
References
Cliques in High-Dimensional Random Geometric Graphs
1 Introduction
2 Auxiliary Results
3 Clique Number in the Sparse Regime
4 Number of Triangles in the Sparse Regime
5 Conclusion
References
Universal Boolean Logic in Cascading Networks
Abstract
1 Introduction
2 The Global Cascade Model (GCM)
3 The Antagonistic Global Cascade Model (AGCM)
4 Boolean Circuits and Functional Completeness
5 Determinism
6 Cascade Frequency
7 Discussion
8 Conclusion
References
Fitness-Weighted Preferential Attachment with Varying Number of New Connections
1 Introduction
2 Attachment with Power Law Growth
3 Degree Dynamics
4 Degree Distribution
5 Expected Average Degree
6 Conclusions
References
Rigid Graph Alignment
1 Introduction and Motivation
2 Problem Formulation
2.1 Problem Definition
2.2 Rigid Graph Matching Algorithm
2.3 Analyzing the Human Functional Connectome
3 Related Literature
References
Detecting Hotspots on Networks
1 Introduction
2 Preliminaries
3 Theoritical Framework
4 Event Concentration Criterion
5 Conclusions
References
Political Networks
A Transparent Referendum Protocol with Immutable Proceedings and Verifiable Outcome for Trustless Networks
1 Introduction
2 Related Work
3 Our Model
3.1 Participants
3.2 Ledger
3.3 Message Notation
3.4 Adversary Model
3.5 Objectives
4 The Protocol
4.1 Protocol Overview
4.2 Protocol Outline
5 Analysis of Objective Fulfillment
5.1 Immutability of the Referendum Proceedings
5.2 Confidentiality of Votes
5.3 Referendum Validation
5.4 Transparency
6 Security Analysis
7 Conclusion
References
Utilizing Complex Networks for Event Detection in Heterogeneous High-Volume News Streams
1 Introduction
2 Related Work
3 Method: Network Event Detection (NED) for News Streams
3.1 Entity Detection
3.2 Knowledge Graph Creation
3.3 Graph Time Series Analysis
3.4 Summarizing the Detected Events
4 Evaluation Method
4.1 Evaluation Against the FA Cup Final Tweet Dataset
4.2 Evaluation Against the All the News Data Set
5 Evaluation Results
6 Event Summarisation
7 Discussion
References
Drawing Networks of Political Leaders: Global Affairs in The Economist's KAL's Cartoons
Abstract
1 Introduction
2 Data
2.1 Case Selection
2.2 From Editorial Cartoons to Network Data
3 Drawing Networks of Political Leaders
3.1 What We Know Without Networks
3.2 Thematic Networks
3.3 Networks of Political Leaders and States
3.4 Multiplex Networks
4 Conclusion
References
Shielding and Shadowing: A Tale of Two Strategies for Opinion Control in the Voting Dynamics
1 Introduction
2 Model and Methods
3 Results
3.1 Numerical Results
3.2 Analytical and Numerical Results on K-Regular Graphs
4 Conclusions
References
Resilience and Control
Stable and Uniform Resource Allocation Strategies for Network Processes Using Vertex Energy Gradients
1 Introduction
2 Basic Definitions
3 Methods
3.1 Resource Exchange Process
3.2 Synthetic Networks
3.3 Empirical Networks
3.4 Measures of Allocation Stability
3.5 Initial Allocations
4 Discussion
5 Conclusions
References
Cascading Failures in Weighted Networks with the Harmonic Closeness
Abstract
1 Introduction
2 Modeling Cascading Failures in Weighted Networks with the Harmonic Closeness
3 Simulation Results and Analysis
4 Case Study
5 Conclusion
Acknowledgements
References
Learning to Control Random Boolean Networks: A Deep Reinforcement Learning Approach
Abstract
1 Introduction
2 Related Work
3 Random Boolean Networks
3.1 Structure and Dynamics
3.2 Attractors
3.3 Example
4 Control of RBNs: Problem Formulation
4.1 Intervention
4.2 Markov Decision Process
5 Double Deep Q Network with Prioritized Experience Replay
5.1 Q Learning
5.2 Double Deep Q Network (Double DQN)
5.3 Prioritized Experience Replay
5.4 Importance of Learning to Control with Model Free RL
6 Experiments and Results
6.1 Random Boolean Network
6.2 Double DQN and Prioritized Experience Replay
6.3 Results
6.4 Conclusion and Future Work
References
Comparative Network Robustness Evaluation of Link Attacks
1 Introduction
2 Preliminaries
3 Motivation of Our Link Attack Strategy
4 Robustness Measures in Complex Networks
5 Performance Evaluation
5.1 Case Study: Effective Resistance on an Internet Backbone
5.2 Comparative Analysis of Different Link Removal Strategies
6 Conclusion
References
MAC: Multilevel Autonomous Clustering for Topologically Distributed Anomaly Detection
Abstract
1 Introduction
2 Problem Setting and Background
3 MAC: Multilevel Autonomous Clustering
3.1 A Node-Based Interpretation
3.2 Extension to Weighted Graphs
3.3 Tuning Parameters
4 Clustering Performance on Test Graphs
5 Benchmarking for Anomaly Detection
6 General Discussion and Future Work
Acknowledgements
References
Network Strengthening Against Malicious Attacks
1 Introduction
2 Model
3 Literature Review
4 Method
5 Results
6 Conclusion
References
Identifying Vulnerable Nodes to Cascading Failures: Optimization-Based Approach
1 Introduction
2 System Model
3 Approximation of Cascading Failure Probabilities
4 Proposed Approach
5 Numerical Results
5.1 Synthetic Scale-Free Networks
5.2 Real Networks
6 Conclusion
References
Ensemble Approach for Generalized Network Dismantling
1 Introduction
2 Network Dismantling Approaches
3 Ensemble-GND Algorithm
4 Conclusion
References
Machine Learning and Networks
A Simple Approach to Attributed Graph Embedding via Enhanced Autoencoder
1 Introduction
2 Related Work
3 Preliminaries and Problem Definition
4 Model
5 Experiments
5.1 Datasets
5.2 Baselines
5.3 Vertex Classification
5.4 Link Prediction
5.5 Network Reconstruction
5.6 Algorithmic and Scalability Analysis
6 Conclusion
References
Matching Node Embeddings Using Valid Assignment Kernels
1 Introduction
2 Preliminaries
2.1 Node Embeddings
2.2 Strong Kernels and Hierarchies
3 Proposed Kernel
3.1 From Vectors to Hierarchies
3.2 Kernel Computation
4 Experimental Evaluation
4.1 Datasets
4.2 Experimental Setup
4.3 Results
5 Conclusion
References
Short Text Tagging Using Nested Stochastic Block Model: A Yelp Case Study
1 Introduction
2 Related Work
3 Dataset Description
4 Short Text Tagging Model
4.1 Modeling Descriptor Similarity
4.2 Tagging via Iterative Nested Stochastic Block Model
5 Method Evaluation
6 Conclusion and Future Work
References
Domain-Invariant Latent Representation Discovers Roles
1 Introduction
2 Related Work
2.1 Role Discovery
2.2 Domain Adaptation
3 Proposed Method
3.1 Notation
3.2 Proposed Model
4 Experiment
4.1 Baseline Model
4.2 Parameter Settings
4.3 Barbell Graph
4.4 Air-Traffic Network
5 Conclusion
References
Inductive Representation Learning on Feature Rich Complex Networks for Churn Prediction in Telco
1 Introduction
2 GraphSAGE
3 Experimental Setup
3.1 Preprocessing the Data
3.2 GraphSAGE Setup
3.3 Local Models
3.4 Performance Measurement
4 Results
4.1 Comparison of Feature Performance
4.2 Comparison of Model Performance
5 Conclusion
References
On Inferring Monthly Expenses of Social Media Users: Towards Data and Approaches
1 Introduction
2 Related Work
3 Dataset and Preprocessing
3.1 Pseudonymization of Financial and Social Media Data
3.2 Graph Extraction
3.3 Identification of Monthly Expenses
4 Method
4.1 Demographic and Local Topology Features
4.2 Network Inference Approaches
4.3 Text Features
4.4 Subscriptions on Public Pages as Features
5 Results
5.1 Demographic and Local Topology Features
5.2 Network Inference Approaches
5.3 Text Features
5.4 Subscriptions
5.5 Combinations of Feature Representations
6 Conclusion
References
Evaluating the Community Structures from Network Images Using Neural Networks
1 Introduction
2 Related Work
3 Methods
3.1 Overview
3.2 Generating Training and Validation Data
3.3 Deep Learning Model
3.4 Performance Measures
4 Experimental Evaluation
4.1 Datasets
4.2 Experimental Setup
4.3 Identifying the Number of Communities
4.4 Predicting the Modularity Score
5 Conclusions
References
Gumbel-Softmax Optimization: A Simple General Framework for Combinatorial Optimization Problems on Graphs
1 Introduction
2 Preliminary
3 Methodology
4 Experiment
5 Conclusion
References
TemporalNode2vec: Temporal Node Embedding in Temporal Networks
1 Introduction
2 Problem Definition
3 TemporalNode2vec
3.1 Random Walks
3.2 PPMI Matrices
3.3 Objective Function Components
3.4 Objective Function Optimization
3.5 Temporal Embeddings Initialization
4 Experiments
4.1 Baseline Methods
4.2 Datasets
4.3 Application Scenarios
4.4 Comparison Results
4.5 Hyper Parameter Analysis
4.6 Alignment
4.7 Embedding Dimension
5 Conclusion
References
Deep Reinforcement Learning for Task-Driven Discovery of Incomplete Networks
1 Introduction
2 Related Work
3 Problem Definition
4 Network Actor Critic (NAC) Algorithm
4.1 Offline Learning and Policy Optimization
4.2 Truncated Node Rank Embedding
5 Experiments
5.1 Datasets
5.2 Baselines
5.3 Learning Scenarios
6 Conclusions and Future Work
References
Evaluating Network Embedding Models for Machine Learning Tasks
Abstract
1 Introduction
2 Related Work
3 Analysis
3.1 Preliminaries
3.2 Contributions
4 Experimental Design
4.1 Datasets
4.2 Experimental Settings
5 Experimental Analysis and Results
5.1 Community Clustering Task
5.2 Link Prediction
6 Discussion and Conclusion
References
A BERT-Based Transfer Learning Approach for Hate Speech Detection in Online Social Media
1 Introduction
2 Previous Works
3 Methodology
3.1 Fine-Tuning Strategies
4 Experiments and Results
4.1 Dataset Description
4.2 Pre-processing
4.3 Implementation and Results Analysis
4.4 Error Analysis
5 Conclusion
References
Network Geometry
A Simple Differential Geometry for Networks and Its Generalizations
1 Introduction
2 Menger Curvature
3 Haantjes Curvature
3.1 A Local Gauss-Bonnet Theorem and the Curvature of 2-Cells
3.2 The Case of General Weights
3.3 A Further Generalization
3.4 Simplified Versions for Simplicial Complexes
4 Conclusions and Further Work
References
Characterizing Distances of Networks on the Tensor Manifold
1 Introduction
2 Preliminaries
2.1 Geodesics on the Network Manifold
2.2 Revisiting Riemannian Framework for Tensors
2.3 Mean, Variance, and Gaussian Distributions
3 Application to Network Characterization
3.1 Network Robustness from Scalar to Matrix Setting
3.2 Appropriate Matrix-Based Model: Graph Laplacian
4 Results
4.1 Toy Network Configurations
4.2 Scale-Free and Random Networks
4.3 Waddingtons Landscape: Cell Differentiation
5 Conclusion
References
Eigenvalues and Spectral Dimension of Random Geometric Graphs in Thermodynamic Regime
1 Introduction
2 Definitions and Preliminary Results on the Eigenvalues of RGG
3 Spectral Dimension of RGG
4 Conclusions
References
Author Index

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