Complex Networks & Their Applications XII [[electronic resource] ] : Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023, Volume 3 / / edited by Hocine Cherifi, Luis M. Rocha, Chantal Cherifi, Murat Donduran

• Autore: Cherifi Hocine
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (501 pages)
• Disciplina: 515.39
• Soggetto topico: Dynamics; Nonlinear theories; Computational intelligence; Applied Dynamical Systems; Computational Intelligence
• Altri autori: RochaLuis M CherifiChantal DonduranMurat
• Nota di contenuto: 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.
• Sommario/riassunto: 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 XII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2023). The carefully selected papers cover a wide range of theoretical topics such as network embedding and network geometry; community structure, network dynamics; diffusion, epidemics and spreading processes; machine learning and graph neural networks as well as all the main network applications, including social and political networks; networks in finance and economics; biological networks and technological networks.
• Titolo autorizzato: Complex Networks & Their Applications XII
• ISBN: 3-031-53472-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910838287203321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in Computational Intelligence, . 1860-9503 ; ; 1143