Complex Networks & Their Applications XII

Name: Complex Networks & Their Applications XII | Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023, Volume 3
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Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023, Volume 3

Hocine Cherifi Luis M. Rocha Chantal Cherifi Murat Donduran(Editor)

Springer (Publisher)

Published on 20. February 2024

XXII, 484 pages

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978-3-031-53472-0 (ISBN)

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Luis M. Rocha is the George J. Klir Professor of Systems Science at the Thomas J. Watson College of Engineering and Applied Science (Department of Systems Science and Industrial Engineering), Binghamton University (State University of New York), where he leads the Complex Adaptive Systems and Computational Intelligence (CASCI) lab. He is also Senior Fellow at the Instituto Gulbenkian da Ciencia, co-director of the Consortium for Social and Biomedical Complexity between Binghamton University and Indiana University, and a founding partner of the international Center for Excellence in Mental Health Sciences. He has been the director of the NSF-NRT Interdisciplinary Training Program in Complex Networks and Systems, and Professor of Informatics in the Luddy School of Informatics, Computing, and Engineering at Indiana University, where he was a member of the advisory council of the Indiana University Network Science Institute, and core faculty of the Cognitive Science Program. Dr. Rocha is a Fulbright Scholar and has been a Visiting Professor a the Center for Theoretical Physics at the Aix-Marseille University, France as well as the Neuroscience Program, at the Champalimaud Foundation and the NOVA School of Business and Economics in Portugal. His research is on complex networks & systems, computational & systems biology, and computational intelligence. He received his Ph.D in Systems Science in 1997 from the State University of New York at Binghamton. From 1998 to 2004, he was a permanent staff scientist at the Los Alamos National Laboratory, where he founded and led a Complex Systems Modeling Team from 1998 to 2002 and was part of the Santa Fe Institute research community. He has organized major conferences in the field, such as the Tenth International Conferenceon the Simulation and Synthesis of Living Systems (Alife X), the Ninth European Conference on Artificial Life (ECAL 2007), and Complex Networks 2019-2023. He has published many articles in scientific and technology journals and has been the recipient of several scholarships and awards. At Indiana University, he has received the Indiana University School of Informatics & Computing, Trustees Award for Teaching Excellence in 2006 and 2015 after developing the complex systems training program and syllabi for several courses.

Hocine Cherifi received the Ph.D. from the National Polytechnic Institute, Grenoble, in 1984. He has been a professor of computer science at the University of Burgundy, Dijon, France, since 1999. Before moving to Dijon, he held faculty positions with Rouen University and Jean Monnet University, France. He has also held visiting positions with Yonsei University, South Korea; the University of Western Australia, Australia; the National Pintung University, Taiwan; and Galatasaray University, Turkey. He has published over 200 scientific papers in international refereed journals and conference proceedings. His current research interests include computer vision and complex networks. He held leading positions in more than 15 international conference organizations as the general chair and the program chair. He has served on more than 100 program committees. He is the Founder of the International Conference on Complex Networks and their Applications. He is a member of the editorial board of Computational Social Networks, PLOS One, IEEE Access, Journal of Imaging, Complex Systems, Quality and Quantity, and Scientific Reports. He is the Founding Editor-in-Chief of Applied Network Science and PLOS Complex Systems.

Chantal CHERIFI received her PhD in Computer science from Corsica University, France, in 2011. Since 2014, she has worked as an Associate Professor at the DISP laboratory at the University of Lyon 2, France. Her main research interests are information systems agility and big data management with applications on enterprise information systems and smart cities, using complex networks, ontologies, and Product Lifecycle Management (PLM) systems tools. She is involved in several International conference organizations: Complex Networks (Program Chair & Local Committee 2017, Poster Chair 2016), CompleNet 2016 (Poster Chair), PLM 2015 (Local Committee), and DICTAP 2011 (Local Committee). She serves as a member of International Conferences Program committees (Complex Networks [2017, 2016], CompletNet 2016, Complexis 2016, ISCRAM-med [2017, 2016, 2015], CSCESM 2014, SITIS [2015, 2014, 2013, 2012], ICIEIS [2013, 2011]) and Journal referee (IJCIM 2016, EPL 2015, Scientific Reports - Nature 2015) She is a member of EU Erasmus-Mundus programs (SmartLink (2012-2016), cLink program (2012-2016)). Her local responsibilities include being a Committee Lab member (Since 2016) and Lab seminar coorganizer (Since 2014).

Murat Donduran is a Professor of Economics at the Department of Economics, YILDIZ Technical University Istanbul Türkiye, where he is the Director of the Graduate School of Social Sciences. He is also the Board member of in Turkish Economic Foundation. His research is on microeconomics, computational economics, firm dynamics and game theory. He received his Bachelor's and Master's Degrees in Economics from Marmara University, Istanbul, Türkiye, and a Ph.D. in Economics in 2000 from the YILDIZ Technical University. Since 2000 he has been a faculty member in the Faculty of Economic and Administrative Sciences at the YILDIZ Technical University. He has organized several conferences in the field such as YILDIZ International Conference on Social Sciences, the Annual International Conference on Social Sciences (2016-2020), and the International Conference on Economics (IceTea) 2019-2023. He has published many articles in scientific journals such as Games and Economic Behavior, Review of Industrial Organization, Physica A, and North American Journal of Economics and Finance.

Content

Intro
Preface
Organization and Committees
Contents
Multilayer/Multiplex
Eigenvector Centrality for Multilayer Networks with Dependent Node Importance
1 Eigenvector Centrality for Multilayer Networks
2 Eigenvector Centrality for Multilayer Networks with Inter-layer Constraints on Adjacent Node Importance
3 Interleaved Power Iteration Algorithm for a System of Dependent Pseudo-eigenvalue Problems
4 Simple Example
5 Random Graph Example
6 Applications and Future Directions
References
Identifying Contextualized Focal Structures in Multisource Social Networks by Leveraging Knowledge Graphs
1 Introduction
2 Literature Review
3 Method of the Study
3.1 Data Collection
3.2 Multisource Knowledge Graph Model
3.3 KG-CSFA
4 Discussion
4.1 Contextual Focal Structure Analysis
5 Conclusion and Future Research
References
How Information Spreads Through Multi-layer Networks: A Case Study of Rural Uganda
1 Introduction
2 Village Networks
3 Use of Village Social Networks to Discuss Refugees
4 When Are Links Most Likely to Be Used?
5 Conclusion
References
Classification of Following Intentions Using Multi-layer Motif Analysis of Communication Density and Symmetry Among Users
1 Introduction
2 Related Work
2.1 Follow Intention Classification
2.2 Twitter Communication Analysis
2.3 Motif Analysis
3 Proposed Method
3.1 Symmetry of Communication Density
3.2 Multi-layer Motif
3.3 Follow Intention Classification
4 Experimental Evaluation
4.1 Dataset
4.2 Results
5 Conclusion
References
Generalized Densest Subgraph in Multiplex Networks
1 Introduction
2 Related Work and Background
3 p-Mean Multiplex Densest Subgraph
3.1 Generalized FirmCore Decomposition
3.2 Approximation Algorithms
4 Experiments
5 Conclusion
References
Influence Robustness of Nodes in Multiplex Networks Against Attacks
1 Introduction
2 Related Work
2.1 Node Centrality Measures
2.2 Network Resilience
3 Proposed Node Centrality
3.1 Preliminaries
3.2 MultiCoreRank Centrality
4 Empirical Analysis of Influence Robustness of Nodes in Multiplex Networks
4.1 Multiplex Network Assortativity
4.2 Datasets
4.3 Effectiveness of the Proposed Centrality
4.4 Influence Robustness of Nodes
5 Conclusion
References
Efficient Complex Network Representation Using Prime Numbers
1 Introduction
2 Methodology
2.1 Definition
2.2 A Simple Example
2.3 Moving to Multi-hop Relationships
3 Applications
3.1 Calculating Prime Adjacency Matrices
3.2 Relation Prediction
3.3 Graph Classification
4 Conclusions
References
Network Analysis
Approximation Algorithms for k-Median Problems on Complex Networks: Theory and Practice
1 Introduction
2 Notation and Definitions
3 Approximation Algorithms and Related Problems
3.1 Degree Ordering
3.2 Extended Degree Ordering
3.3 PageRank Ordering
3.4 VoteRank Ordering
3.5 Coreness Ordering
3.6 Extended Coreness Ordering
3.7 H-Index Ordering
3.8 Expected Value (Random)
4 Experiments and Methodology
5 Results
5.1 Comparisons with Optimal k-median solutions
5.2 Case Studies: Million-Node Networks
5.3 Overall Results
6 Conclusion
References
Score and Rank Semi-monotonicity for Closeness, Betweenness and Harmonic Centrality
1 Introduction and Definitions
2 Distances and Basins
3 Closeness Centrality
4 Harmonic Centrality
5 Betweenness Centrality
6 Conclusions and Future Work
References
Non Parametric Differential Network Analysis for Biological Data
1 Introduction
2 Related Work
3 The Proposed Pipeline
3.1 Non Parametric Differential Network Analysis
4 Experimental Results
5 Conclusion
References
Bowlership: Examining the Existence of Bowler Synergies in Cricket
1 Introduction
2 Methodology
2.1 Mann-Whitney U Test
2.2 Bowlership Networks
3 Results
4 Conclusion
References
A Correction to the Heuristic Algorithm MinimalFlipSet to Balance Unbalanced Graphs
1 The Problem of Balancing an Unbalanced Graph
2 Preliminaries
2.1 Verifying Balancedness of G via the Node Labels s(x)
2.2 An Algorithm for EmalFlip by Alabandi et al.
3 Flipping Edges in T to Balance G
3.1 Selection Criteria for an Edge (u, v) T for Flipping
3.2 Corrected Form of MinimalFlipSet in ch12kundu2022nanavati
3.3 Repeated Flipping of an Edge
4 Conclusion
References
Influential Node Detection on Graph on Event Sequence
1 Introduction
2 Proposed Method
2.1 Graph on Event Sequence
2.2 Hawkes Process for Influence Measurement
2.3 Soft K-Shell Algorithm
3 Experiments and Results
3.1 SIR Simulation Results
3.2 Computational Complexity Results
3.3 Soft Shell Decomposition
4 Conclusion
References
Decentralized Control Methods in Hypergraph Distributed Optimization
1 Introduction
2 Preliminaries
2.1 Notation
2.2 Non Linear Control Theory
2.3 Hypergraphs
2.4 Optimization Theory
2.5 Matrix Theory
3 The Hypergraph Distributed Optimization Problem
4 Primal Dual Algorithm
4.1 Directed Weighted Laplacian
5 Conclusion
References
Topic-Based Analysis of Structural Transitions of Temporal Hypergraphs Derived from Recipe Sharing Sites
1 Introduction
2 Related Work
3 Preliminaries
3.1 Temporal Hypergraphs of Recipe Streams
3.2 Structural Transitions of Temporal Hypergraphs
4 Analysis Method
4.1 Extraction of Topics
4.2 Topic-Based Analysis of Structural Transitions
5 Experiments
5.1 Datasets and Experimental Settings
5.2 Evaluation of Proposed Model
5.3 Analysis Results
6 Conclusion
References
I Like You if You Are Like Me: How the Italians' Opinion on Twitter About Migrants Changed After the 2022 Russo-Ukrainian Conflict
1 Introduction
2 Related Work
3 Italians' Perception of Migrants on Twitter
4 Conclusions
References
Modeling the Association Between Physician Risky-Prescribing and the Complex Network Structure of Physician Shared-Patient Relationships
1 Introduction
2 Methods
2.1 Study Overview
2.2 Exponential Random Graph Models (ERGMs)
2.3 New Network Statistics: Triadic Homophily Associated with Risky Prescribing
2.4 Non-parametric Test for Triadic Homophily
3 Application to Study of Homophily in Physician Prescribing and Deprescribing
4 Results
4.1 Physician Shared-Patient Networks
4.2 ERGMs for Adjusted Homophily
4.3 Triadic-Level Hyper Homophily
5 Conclusions
References
Focal Structures Behavior in Dynamic Social Networks
1 Introduction
2 Related Work
3 Methodology
3.1 Definitions
3.2 Validation and Verification
4 Results
4.1 Development of the Campaign on Twitter Over Time
4.2 Focal Structure Analysis in Dynamic Networks
4.3 Validation and Evaluation in Dynamic Social Networks
5 Conclusion
References
Unified Logic Maze Generation Using Network Science
1 Introduction and Related Work
2 Modeling Logic Mazes
3 Maze Characteristics
3.1 Paths, Branching, Reachability
3.2 Traps and Holes
3.3 Decisions, Required Vertices, Bridges/Dominance
4 Local Search Generation
5 Example Objective Function
6 Results
7 Conclusions and Future Work
References
INDoRI: Indian Dataset of Recipes and Ingredients and Its Ingredient Network
1 Introduction
2 Literature Survey
3 Indian Dataset of Recipes and Ingredients (INDoRI)
3.1 Ingredient Network Construction
3.2 Communities in InN
4 Applications on INDoRI and InN
4.1 Example: Community Detection for Better Categorization of Ingredients
5 Conclusion
References
Optimizing Neonatal Respiratory Support Through Network Modeling: A New Approach to Post-birth Infant Care
1 Introduction
2 Background Literature
3 Modeling Approach for Neonatal Respiratory Support
4 Findings from Network Model Simulations
5 Discussion
References
Generalized Gromov Wasserstein Distance for Seed-Informed Network Alignment
1 Introduction
2 Background
2.1 Optimal Transport
2.2 Gromov-Wasserstein Distance
2.3 Network Alignment Problem
3 Methods
3.1 Generalized Gromov-Wasserstein with Known Matching Nodes
3.2 Seeded Network Alignment Using Optimal Transport
4 Experimental Results
4.1 Datasets
4.2 Baseline Methods
4.3 Experimental Setup
4.4 Results on Real Network Pairs
4.5 Results on Simulated Pairs of Networks
5 Conclusions
References
Orderliness of Navigation Patterns in Hyperbolic Complex Networks
1 Introduction
2 Related Works
2.1 Hyperbolic Geometry of Complex Networks
2.2 Modeling Forwarding Tables
2.3 Measures to Orderliness
3 Data Sets
3.1 Synthetic Network Generation
3.2 Internet AS-Level Topology - A Real World Example
4 Methods
4.1 Ordering IDs According to the Hyperbolic Angular Coordinates
4.2 Ordering IDs Based on Hierarchical Clustering
5 Discussion
6 Conclusion
References
Multiplex Financial Network Regionalization Scenarios as a Result of Re-globalization: Does Geographical Proximity Still Matter?
1 Introduction
2 Literature
3 Methodology
3.1 Logics and Methods
3.2 Data
4 Results
4.1 Geographical Regionalization
4.2 Bipolar Regionalization
5 Conclusions and Discussion
References
A Modular Network Exploration of Backbone Extraction Techniques
1 Introduction
2 Backbone Extraction Methods
3 Data and Methods
3.1 Data
3.2 Methods
4 Experimental Results
4.1 Backbones Basic Topological Properties
4.2 Qualitative Comparisons of the Backbones Community Structure
4.3 Preserving Inter or Intra-community Edges
4.4 The Backbone Power in Revealing the US-ES Communities
5 Discussion
6 Conclusion
References
IS-PEW: Identifying Influential Spreaders Using Potential Edge Weight in Complex Networks
1 Introduction
2 Baseline Centrality Methods
2.1 Research Motivation
3 Proposed Method: IS-PEW
3.1 Connectivity Structure
3.2 Ability of Information Exchange
3.3 Importance of Neighbouring Nodes
3.4 Calculation of the Influential Spreaders
3.5 Algorithm Details
3.6 Computational Complexity
4 Methodology to Evaluate IS-PEW
4.1 Dataset Description
4.2 Tools
4.3 Experiments
5 Results and Analysis
6 Conclusion
References
Robustness of Centrality Measures Under Incomplete Data
1 Introduction
2 Methodology
2.1 Preliminaries
2.2 Centrality Measures
2.3 Imputation Methods and Performance Analysis
3 Robustness of Centrality Measures in Real Networks
3.1 The Analysis of the Criminal Network
3.2 The Analysis of Food Trade Network
4 Discussion
References
ATEM: A Topic Evolution Model for the Detection of Emerging Topics in Scientific Archives
1 Introduction
2 Evolution Analysis in Scientific Archives
3 ATEM Framework
3.1 Extracting Evolving Topics
3.2 Creating Evolving Topic-Citation Graph
3.3 Extracting Emerging Topics
4 Implementation
5 Proof of Concept
6 Conclusion
References
Analysis and Characterization of ERC-20 Token Network Topologies
1 Introduction
2 Background
3 Transfer Event Graph
4 Experimental Results
4.1 Global Analysis
4.2 Graph Construction
4.3 Graph Analysis
4.4 Clustering
5 Conclusions and Future Work
References
Network Geometry
Modeling the Invisible Internet
1 Introduction
2 Backgound: Descriptive Explanation of Garlic Routing and I2P Tunneling
3 Weighted Random Sampling Without Replacement
4 Tunnel Formation in Complete Graph
5 I2P Network Structure
6 Validation
7 Conclusion
References
Modeling the Dynamics of Bitcoin Overlay Network
1 Introduction
2 Related Work
3 Evolutionary Random Graph
4 Key Graph Properties
5 Verification of Key Graph Properties
5.1 Verification: Diameter and Radius
5.2 Verification: Coverage
6 Conclusion
References
Graph Based Approach for Galaxy Filament Extraction
1 Introduction
2 Preliminaries
2.1 Density Estimator and Density Levels
3 Our Method
3.1 Theoretical Advantage: The Percolation Rate
3.2 Filament Extraction from a Graph
3.3 The Density Level Estimator
4 Results
5 Conclusion and Perspectives
References
Metric Invariants for Networks' Classification
1 Introduction
2 The Invariants
3 Experiments
3.1 The Data Sets
4 Conclusions and Future Study
References
The Hidden-Degree Geometric Block Model
1 Introduction
1.1 Related Work
2 Methods
2.1 Hyperbolic Geometric Models
2.2 The HGBM Model
3 Simulation-Based Analysis
3.1 Block Mixing
3.2 Degree Distribution
3.3 Local Clustering Distribution
4 Conclusions
References
Networks in Finance and Economics
Interactions Within Complex Economic System
1 Introduction
2 Economic System as Random Dynamic Chaotic One
2.1 Complex Economic Systems as Lorenz-System
2.2 Lorenz-Systems as Economic Bifurcation
3 Economic Network Formation Similar to Neuron Formation
4 Conclusions
References
Demand Shocks and Export Surges in Trade Networks
1 Introduction
2 Theory
3 Data
4 Research Design
5 Results
6 Conclusion
References
Properties of B2B Invoice Graphs and Detection of Structures
1 Introduction
2 B2B Invoice Graphs: Definition and Properties
2.1 Comparative Study of Our Datasets
2.2 Statistical Study on Monthly Graphs
2.3 Comparison with Well-Known Families of Graphs
2.4 Distribution of Degrees and Weights
3 Communities Detection in B2B Invoice Graphs
3.1 Two Direct Methods for Communities Detection
3.2 Communities Detection Using Modularity
4 Conclusion
References
A Model and Structural Analysis of Networked Bitcoin Transaction Flows
1 Background and Motivation
2 Construction of Networked Transaction Flows as Directed Acyclic Graphs (DAGs)
3 Activity Measures
4 Materials and Methods
4.1 Data
5 Experiments
5.1 Growing and Saturating Stages
5.2 Analysis in 2013
6 Conclusion
References
Rank Is All You Need: Robust Estimation of Complex Causal Networks
1 Introduction
2 Related Work
3 Methodology/Constructing Networks
3.1 Pearson and Spearman Correlation
3.2 Vector Autoregression
3.3 Rank Vector Autoregression
4 Simulation Methodology
4.1 Simulating VAR Processes
4.2 Variations on VAR Processes
5 Simulation-Based Validation
5.1 ROC Analysis
5.2 Classification Analysis
6 Empirical Data Analysis
6.1 Data
6.2 Empirical Networks
7 Conclusion
References
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Complex Networks & Their Applications XII

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