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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
| 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 |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (501 pages) |
| Disciplina | 515.39 |
| Altri autori (Persone) |
RochaLuis M
CherifiChantal DonduranMurat |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Dynamics
Nonlinear theories Computational intelligence Applied Dynamical Systems Computational Intelligence |
| ISBN | 3-031-53472-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| 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. |
| Record Nr. | UNINA-9910838287203321 |
Cherifi Hocine
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Complex Networks & Their Applications XII [[electronic resource] ] : Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023 Volume 1 / / edited by Hocine Cherifi, Luis M. Rocha, Chantal Cherifi, Murat Donduran
| Complex Networks & Their Applications XII [[electronic resource] ] : Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023 Volume 1 / / edited by Hocine Cherifi, Luis M. Rocha, Chantal Cherifi, Murat Donduran |
| Autore | Cherifi Hocine |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (482 pages) |
| Disciplina | 515.39 |
| Altri autori (Persone) |
RochaLuis M
CherifiChantal DonduranMurat |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Dynamics
Nonlinear theories Computational intelligence Applied Dynamical Systems Computational Intelligence |
| ISBN | 3-031-53468-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910838285603321 |
|
Cherifi Hocine
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||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Complex Networks and Their Applications VII [[electronic resource] ] : Volume 1 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018 / / edited by Luca Maria Aiello, Chantal Cherifi, Hocine Cherifi, Renaud Lambiotte, Pietro Lió, Luis M. Rocha
| Complex Networks and Their Applications VII [[electronic resource] ] : Volume 1 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018 / / edited by Luca Maria Aiello, Chantal Cherifi, Hocine Cherifi, Renaud Lambiotte, Pietro Lió, Luis M. Rocha |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXVII, 893 p. 291 illus., 250 illus. in color.) |
| Disciplina | 006.3019 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-030-05411-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484846403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Complex Networks and Their Applications VII [[electronic resource] ] : Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018 / / edited by Luca Maria Aiello, Chantal Cherifi, Hocine Cherifi, Renaud Lambiotte, Pietro Lió, Luis M. Rocha
| Complex Networks and Their Applications VII [[electronic resource] ] : Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018 / / edited by Luca Maria Aiello, Chantal Cherifi, Hocine Cherifi, Renaud Lambiotte, Pietro Lió, Luis M. Rocha |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXV, 677 p. 217 illus., 158 illus. in color.) |
| Disciplina | 001.64404 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-030-05414-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484846303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Complex Networks and Their Applications XII : Proceedings of the Twelfth International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2023, Volume 2
| Complex Networks and Their Applications XII : Proceedings of the Twelfth International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2023, Volume 2 |
| Autore | Cherifi Hocine |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (523 pages) |
| Altri autori (Persone) |
RochaLuis M
CherifiChantal DonduranMurat |
| Collana | Studies in Computational Intelligence Series |
| ISBN | 3-031-53499-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization and Committees -- Contents -- Community Structure -- Identifying Well-Connected Communities in Real-World and Synthetic Networks -- 1 Introduction -- 2 Results -- 2.1 Initial Observations -- 2.2 Connectivity Modifier -- 2.3 Effect of CM on Clustered Real World Networks -- 2.4 Synthetic LFR Networks -- 3 Discussion -- References -- Bayesian Hierarchical Network Autocorrelation Models for Modeling the Diffusion of Hospital-Level Quality of Care -- 1 Introduction -- 2 Notation and Models -- 2.1 Hierarchical Network Autocorrelation Model -- 2.2 Extended Hierarchical Network Autocorrelation Model -- 2.3 Illustration of Marginal Mean and Variance of Extended Model with Simulated Data -- 3 Bayesian Hierarchical Network Autocorrelation Model and Estimation -- 4 Simulation Study -- 5 The Impact on Patient Quality of Hospitals' Adoption of Robotic Surgery -- 6 Discussion -- References -- Topological Community Detection: A Sheaf-Theoretic Approach -- 1 Introduction -- 2 Background: Sheaves and Social Networks -- 2.1 Sheaves and Sheaf Cohomology -- 2.2 Discourse Sheaves and Opinion Dynamics -- 3 Methods and Experimental Design -- 3.1 Detecting Communities with Constant Sheaves -- 3.2 Convergence of Algorithm 1: Community Detection with Constant Sheaves -- 3.3 Detecting Communities with a Non-constant Sheaf -- 3.4 Deterministic Sheaf Community Detection -- 3.5 Experimental Setup -- 4 Experimental Results -- 5 Discussion -- References -- Does Isolating High-Modularity Communities Prevent Cascading Failure? -- 1 Introduction -- 2 Methods -- 2.1 MSNR -- 2.2 Networks -- 2.3 Dynamics -- 2.4 Quality of Partition -- 3 Results -- 4 Discussion -- References -- Two to Five Truths in Non-negative Matrix Factorization -- 1 Bipartite Laplacian and Other Matrix Scalings -- 2 Computational Results -- 2.1 Three Datasets of Varying Difficulty.
2.2 From Data to Matrices -- 2.3 Clustering with an NMF and Evaluating Performance -- 3 Discussion -- 4 Related Work -- 5 Conclusions -- References -- Adopting Different Strategies for Improving Local Community Detection: A Comparative Study -- 1 Introduction -- 2 Related Work -- 3 Variants of a Local Community Detection with Seeds-0.5em -- 3.1 Preliminaries and Problem Formulation -- 3.2 Proposed Variants -- 4 Experiments -- 4.1 Experiment Design -- 4.2 Experiments on Synthetic and Real Datasets -- 5 Conclusions and Future Scope -- References -- Pyramid as a Core Structure in Social Networks -- 1 Introduction -- 2 Preliminary -- 3 The Proposed Pyramid Structure -- 4 Empirical Studies and Applications -- 4.1 On the Existence of Large Pyramid -- 4.2 A Novel Structural Feature Revealed by Pyramid -- 4.3 Large Pyramid as a Core Structure -- 5 Conclusion -- References -- Dual Communities Characterize Structural Patterns and Robustness in Leaf Venation Networks -- 1 Introduction -- 2 Dual Graphs of Weighted Spatial Networks -- 3 Communities and Hierarchies in Dual Graphs -- 4 Classification of Leaf Venation Patterns -- 5 Dual Communities and Leaf Robustness -- 6 Conclusion -- References -- Tailoring Benchmark Graphs to Real-World Networks for Improved Prediction of Community Detection Performance -- 1 Introduction -- 2 Background -- 2.1 LFR Benchmark Graphs -- 2.2 nPSO Benchmark Graphs -- 2.3 Related Work -- 3 The Real-World Network -- 4 The Real-World Network Compared to Tailored Benchmark Graphs -- 5 Results -- 5.1 Experiments with the Louvain Method -- 5.2 Experiments with Other Community Detection Algorithms -- 5.3 Comparing the Performance on Tailored Benchmark Graphs to the Performance on the Real-World Network -- 6 Conclusion and Discussion -- References. Network Based Methodology for Characterizing Interdisciplinary Expertise in Emerging Research -- 1 Introduction -- 2 Related Work -- 3 Expertise-Collaboration Network (ECN) Methodology -- 3.1 Indicators -- 3.2 Expertise-Collaboration Network (ECN) Model -- 3.3 Measures -- 4 Case-Study: IDR Within RETTL Community -- 4.1 Research Context: RETTL Program -- 4.2 Data Collection -- 4.3 Analyzing Available Expertise in the RETTL Community -- 5 Discussions and Conclusions -- References -- Classification Supported by Community-Aware Node Features -- 1 Introduction -- 2 Community-Aware Node Features -- 2.1 Anomaly Score CADA -- 2.2 Normalized Within-Module Degree and Participation Coefficient -- 2.3 Community Association Strength -- 2.4 Distribution-Based Measures -- 3 Experiments -- 3.1 Graphs Used -- 3.2 Node Features Investigated -- 3.3 Experiments -- References -- Signature-Based Community Detection for Time Series -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Asset Graph -- 3.2 Random Matrix Theory -- 3.3 Community Detection -- 3.4 Signature -- 4 Signature-Based Similarity Matrix -- 5 Experimental Evaluation -- 6 Conclusion -- References -- Hierarchical Overlapping Community Detection for Weighted Networks -- 1 Introduction -- 2 Related Work -- 3 Proposed Algorithm for Overlapping Hierarchical Weighted Community Detection -- 3.1 CT-distance in Weighted 2-edge-connected Graph -- 3.2 Community Detection Procedure -- 4 Experiments -- 4.1 Unweighted Synthetic Networks -- 4.2 Sensitivity of Community Detection Methods to Edge Weight -- 4.3 Weighted Synthetic Network -- 5 Conclusion -- References -- Detecting Community Structures in Patients with Peripheral Nervous System Disorders -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Dataset Description -- 5 Proposed Method -- 5.1 The Projection Phase -- 5.2 Weight Assignment Phase. 5.3 The Community Detection Phase -- 6 Experiments and Results -- 6.1 Results -- References -- Community Detection in Feature-Rich Networks Using Gradient Descent Approach -- 1 Introduction: Background and Modification -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Proposed Clustering Methods -- 3 Experimental Setting -- 3.1 Algorithms Under Comparison -- 3.2 Data Sets -- 3.3 Evaluation Criteria -- 4 Scrutinizing the Main Hyperparameters of the Proposed Methods -- 5 Experimental Results -- 5.1 Comparison over Real-Word Data Sets -- 5.2 Comparison over Synthetic Data with Categorical Features -- 6 Conclusion and Future Work -- References -- Detecting Strong Cliques in Co-authorship Networks -- 1 Introduction -- 2 Strong Cliques -- 2.1 Structural Dependency -- 2.2 Dependency Threshold Estimation -- 3 Experiments -- 3.1 Results and Discussion -- 3.2 Dependency Threshold Effect -- 4 Conclusion and Future Work -- References -- Mosaic Benchmark Networks: Modular Link Streams for Testing Dynamic Community Detection Algorithms -- 1 Introduction -- 2 Related Works -- 3 Mathematical Framework -- 3.1 Link Stream -- 3.2 Mosaic: A Definition for a Community in Link Streams -- 3.3 Mosaic Link Stream Benchmark -- 3.4 Scenario Description -- 3.5 Generating Edges -- 4 Experiments -- 5 Discussion and Conclusions -- References -- Entropic Detection of Chromatic Community Structures -- 1 Introduction -- 2 Formalizing the Coloring -- 3 Chromatic Entropy -- 3.1 Chromatic Entropy Definition -- 3.2 Probability of Random Coloring -- 4 Chromatic Community Structure Detection -- 5 Conclusion -- References -- On the Hierarchical Component Structure of the World Air Transport Network -- 1 Introduction -- 2 Data and Method -- 2.1 Data -- 2.2 Methods -- 3 Experimental Results -- 3.1 Component Structure -- 3.2 First Level of Hierarchy -- 3.3 Second Level of Hierarchy. 4 Discussion -- 5 Conclusion -- References -- Weighted and Unweighted Air Transportation Component Structure: Consistency and Differences -- 1 Introduction -- 2 Mesoscopic Structure Analysis -- 2.1 Community Structure -- 2.2 Component Structure Analysis -- 3 Global Topological Properties of the Components -- 3.1 Clustering Coefficient -- 3.2 Strength Distribution -- 4 Discussion and Conclusion -- References -- Effects of Null Model Choice on Modularity Maximization -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 General Experimental Set of Networks -- 3.2 Fixed Community Size Distribution Experimental Set -- 4 Discussion -- 4.1 Extension to Explicit Multi-level Methods -- 5 Conclusion -- References -- On Centrality and Core in Weighted and Unweighted Air Transport Component Structures -- 1 Introduction -- 2 Core Structure Analysis -- 2.1 Local Components -- 2.2 Global Component -- 2.3 World Air Transportation Network -- 3 Local Topological Properties -- 3.1 Top Five Nodes Analysis -- 3.2 RBO Analysis -- 4 Discussion and Conclusion -- References -- Diffusion and Epidemics -- New Seeding Strategies for the Influence Maximization Problem -- 1 Introduction -- 2 Related Work -- 2.1 Influence Maximization Problem -- 2.2 Diffusion Models -- 2.3 Seeding Strategies for the IMP -- 3 New Seeding Strategies -- 3.1 CVSP: Connectivity-Based Seeding Strategy -- 3.2 ER: Spectral Seeding Strategy -- 4 Comparison Experiments -- 4.1 Experiment Design, Implementation and Data Sets -- 4.2 Final Influence Spreading Rate Comparison -- 4.3 Visual Analysis and Comparison -- 4.4 Summary and Recommendation -- References -- Effects of Homophily in Epidemic Processes -- 1 Introduction -- 2 Basic Setup -- 2.1 Probability of Epidemics -- 3 Model and Main Results -- 3.1 Multi-type Branching Processes -- 3.2 Generating Functions -- 4 Numerical Studies -- 5 Conclusion. A Proof of Theorem 1. |
| Record Nr. | UNINA-9910842288303321 |
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Cherifi Hocine
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| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Complex Networks and Their Applications XII : Proceedings of the Twelfth International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2023, Volume 4
| Complex Networks and Their Applications XII : Proceedings of the Twelfth International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2023, Volume 4 |
| Autore | Cherifi Hocine |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (490 pages) |
| Altri autori (Persone) |
RochaLuis M
CherifiChantal DonduranMurat |
| Collana | Studies in Computational Intelligence Series |
| ISBN | 3-031-53503-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization and Committees -- Contents -- Higher-Order Interactions -- Analyzing Temporal Influence of Burst Vertices in Growing Social Simplicial Complexes -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Proposed Method -- 4.1 Burst Vertices -- 4.2 Proposed Model -- 4.3 Learning Method -- 5 Experiments -- 5.1 Datasets -- 5.2 Empirical Data Analysis -- 5.3 Evaluation of Proposed Model -- 5.4 Analysis of Temporal Influence -- 6 Conclusion -- References -- An Analytical Approximation of Simplicial Complex Distributions in Communication Networks -- 1 Background -- 2 Methodology -- 2.1 Scale-Free Network Growth with Triad Formation -- 2.2 Adjacency Factor -- 3 Experiments -- 4 Conclusion -- References -- A Dynamic Fitting Method for Hybrid Time-Delayed and Uncertain Internally-Coupled Complex Networks: From Kuramoto Model to Neural Mass Model -- 1 Introduction -- 2 Method -- 2.1 Real Human Brain Data Structure -- 2.2 Extended Neural Mass Model with Coupling Strength and Time Delay -- 2.3 Extended Kuramoto Model with Coupling Strength and Time Delay -- 2.4 Dynamic Fitting for Two Extended Model -- 3 Results -- 4 Discussion -- References -- Human Behavior -- An Adaptive Network Model for Learning and Bonding During a Varying in Rhythm Synchronous Joint Action -- 1 Introduction -- 2 The Self-modeling Network Modeling Approach Used -- 3 Design of the Adaptive Network Model -- 4 Simulation Results -- 5 Model Evaluation and Discussion -- References -- An Adaptive Network Model for the Emergence of Group Synchrony and Behavioral Adaptivity for Group Bonding -- 1 Introduction -- 2 Background Research -- 3 Network Representations for Adaptive Dynamical Systems -- 4 A Network Model for Group Synchrony and Group Bonding -- 5 Simulation Results -- 6 Discussion -- References.
Too Overloaded to Use: An Adaptive Network Model of Information Overload During Smartphone App Usage -- 1 Introduction -- 2 Background -- 3 Network-Oriented Modeling -- 4 Adaptive Network Model of Information Overload -- 5 Simulation Results -- 6 Discussion -- References -- Consumer Behaviour Timewise Dependencies Investigation by Means of Transition Graph -- 1 Introduction -- 2 Related Works -- 3 Data Description -- 4 Transition Graph Construction and Applying -- 5 Timewise Dependencies Investigation -- 6 Conclusion and Future Work -- References -- An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations -- 1 Introduction -- 2 Modeling Adaptive Networks as Self-modeling Networks -- 3 Setup of the Computational Analysis -- 4 Simulation Experiments -- 5 Discussion -- 6 Conclusion -- References -- Identification of Writing Preferences in Wikipedia -- 1 Introduction -- 1.1 Writing Preferences in Wikipedia -- 1.2 Genre and Prototype Theory -- 1.3 Prototype and Writing Preferences -- 2 Method -- 2.1 Dataset -- 2.2 Preprocessing of the Dataset -- 2.3 Prototype Identification -- 2.4 The Whole Procedure -- 2.5 Prototype Analysis -- 2.6 Implementation Details -- 3 Results -- 4 Discussion -- References -- Influence of Virtual Tipping and Collection Rate in Social Live Streaming Services -- 1 Introduction -- 2 Related Work -- 3 Proposed Model and Methodology -- 3.1 Overview -- 3.2 SNS-Norms Game with Tip and Quality -- 3.3 Game Process -- 3.4 Evolution of Behavioral Strategies for Individual Agents -- 4 Experiments and Discussion -- 4.1 Experimental Setting -- 4.2 Strategies Under Various Collection Rates -- 4.3 Agents' Utility and Platform's Gain -- 5 Conclusion -- References -- Information Spreading in Social Media -- Algorithmic Amplification of Politics and Engagement Maximization on Social Media. 1 Introduction -- 2 Methods -- 2.1 Engagement Predictive Models -- 2.2 Timelines Simulation -- 2.3 Metrics -- 3 Results -- 3.1 Relative Amplification -- 3.2 Audience Diversity -- 4 Discussion -- References -- Interpretable Cross-Platform Coordination Detection on Social Networks -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Method -- 4.1 Multi-layer Network Community Detection -- 4.2 Cross-Platform Community Alignment -- 4.3 Overview of the Framework -- 5 Results -- 6 Discussion -- References -- Time-Dynamics of (Mis)Information Spread on Social Networks: A COVID-19 Case Study -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection and Dataset Description -- 3.2 Longitudinal Analysis Methods -- 4 Longitudinal Analysis -- 4.1 Tweet Intensity -- 4.2 Mis(information) Longevity in Networks -- 4.3 Short Discussion on Tweet Labels -- 5 Conclusion and Future Work -- References -- A Comparative Analysis of Information Cascade Prediction Using Dynamic Heterogeneous and Homogeneous Graphs -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Problem Definition -- 3.2 Homogeneous Graph Neural Network Model -- 3.3 CasSeq-Model -- 3.4 HetSAGE Model -- 3.5 HetSeq-Model -- 4 Experimental Setup -- 5 Results -- 5.1 Temporal Sequence in Heterogeneous vs. Homogeneous Graph -- 5.2 Edge Selection in Heterogeneous Networks -- 6 Conclusions -- References -- A Tale of Two Cities: Information Diffusion During Environmental Crises in Flint, Michigan and East Palestine, Ohio -- 1 Context and Motivation -- 2 The Informational Nature of Environmental Crises -- 2.1 Environmental Crises in Flint, MI and East Palestine, OH -- 2.2 The Complex Nature of Information Diffusion -- 3 Research Methods -- 3.1 Information Diffusion Model -- 3.2 Simulating Information Spread to Mimic Observed Crises -- 4 Results and Findings. 4.1 Patterns Simulate East Palestine Better Than Flint -- 4.2 Reproduction of Dynamics in the Case of Flint -- 5 Discussion -- 6 Conclusion -- References -- Multilingual Hate Speech Detection Using Semi-supervised Generative Adversarial Network -- 1 Introduction -- 2 Literature Survey -- 2.1 GAN for Hate Speech Detection -- 2.2 GAN-BERT -- 2.3 GAN-BERT for Hate Speech Detection -- 3 Methodology -- 3.1 Semi-supervised Generative Adversarial Network: SS-GAN -- 3.2 SS-GAN-mBERT -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Experiments and Analysis -- 5 Discussions and Future Directions -- 5.1 Discussions -- 5.2 Future Directions -- 6 Conclusion -- References -- Exploring the Power of Weak Ties on Serendipity in Recommender Systems -- 1 Introduction -- 2 Background and Related Work -- 2.1 Serendipity in Recommenders -- 2.2 Recommendations and Social Network Connections -- 3 Community-Based Mechanism -- 4 Results and Discussions -- 5 Conclusions and Future Work -- References -- Infrastructure Networks -- An Interaction-Dependent Model for Probabilistic Cascading Failure -- 1 Introduction -- 2 CASCADE Model and Interaction Graph -- 2.1 CASCADE Model -- 2.2 Interaction Graph -- 3 Interaction-CASCADE Model -- 4 Numerical Studies -- 4.1 Interaction Independent Load Distribution -- 4.2 Interaction-Dependent Load Distribution -- 5 Conclusion and Future Works -- References -- Detecting Critical Streets in Road Networks Based on Topological Representation -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 4 Detection Method -- 4.1 Problem Formulation -- 4.2 Critical Vertices Detection Based on High-Salience Skeleton -- 4.3 Baseline Methods -- 5 Experiments -- 5.1 Datasets and Settings -- 5.2 Results of Street Score Distribution -- 5.3 Comparison Results of Critical Street Detection Methods -- 6 Conclusion -- References. Transport Resilience and Adaptation to Climate Impacts - A Case Study on Agricultural Transport in Brazil -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Conclusion -- References -- Incremental Versus Optimal Design of Water Distribution Networks - The Case of Tree Topologies -- 1 Introduction -- 2 Related Work -- 3 Framework and Metrics -- 4 Tree Networks -- 4.1 Random Expansion -- 4.2 Gradual Expansion -- 5 Case Study -- 6 Conclusion, Limitations and Future Work -- References -- Social Networks -- Retweeting Twitter Hate Speech After Musk Acquisition -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Hate Group Selection -- 3.2 Data Collection and Augmentation -- 3.3 The Filtering of Bot Accounts -- 3.4 Retweet Networks -- 3.5 Configuration Retweet Network Model -- 3.6 T-Test and P-Values -- 4 Results -- 4.1 Comparing the 2021 and 2022 Networks -- 4.2 Retweeters of Elon Musk and Hate Groups -- 5 Discussion -- 6 Conclusion -- References -- Unveiling the Privacy Risk: A Trade-Off Between User Behavior and Information Propagation in Social Media -- 1 Introduction -- 2 Related Work -- 3 Privacy Risk Assessment of Users -- 3.1 The Twitter Dataset and the Labeling Process -- 3.2 Unsupervised Privacy Risk Assessment -- 3.3 Supvervised Privacy Risk Assessment -- 4 Experimental Evaluation -- 4.1 Technical Details and Evaluation Metrics -- 4.2 Results: Unsupervised Privacy Risk Assessment -- 4.3 Results: Supervised Privacy Risk Assessment -- 4.4 Results: Discussion -- 5 Conclusions and Further Research -- References -- An Extended Uniform Placement of Alters on Spherical Surface (U-PASS) Method for Visualizing General Networks -- 1 Introduction -- 2 Notations and Definitions -- 3 Method -- 3.1 Three-Stage Optimization -- 3.2 Spherical Discrepancy -- 4 Performance Comparison -- 5 Real Data Example -- 6 Conclusion -- References. The Friendship Paradox and Social Network Participation. |
| Record Nr. | UNINA-9910842296903321 |
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Cherifi Hocine
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| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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