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 4
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Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023, Volume 4

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

Springer (Publisher)

Published on 28. February 2024

XXII, 474 pages

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978-3-031-53503-1 (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 Lyon2, 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
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
1 Introduction
2 Model Formulation
2.1 Florentine Families Network
3 Simulation Setup
4 Results
4.1 Negative Unit Step Function Simulations
4.2 Continuous Monotonically Decreasing DRFs
4.3 Convex DRFs
4.4 Positive Unit Step Function DRFs
5 Concluding Remarks
5.1 Summary
5.2 Practical Implications for Real-World Networks
5.3 Next Steps and Research Opportunities
References
Dynamics of Toxic Behavior in the Covid-19 Vaccination Debate
1 Introduction
2 Data Processing
3 Network Communities
3.1 Community Detection
3.2 Stability of Communities
3.3 Differences Between Provax and Novax
4 Investigating Toxic Behaviors
4.1 Testing Hypothesis H1
4.2 Testing Hypothesis H2
5 Discussion and Conclusions
References
Improved Change Detection in Longitudinal Social Network Measures Subject to Pattern-of-Life Variations
1 Introduction
2 Background
2.1 Automated Flow for Change Detection
2.2 Pattern-of-Life Variations
2.3 Existing Approaches to Remove Pattern-of-Life Variations Using Fourier Transforms
3 Approach
3.1 Adaptive Multiplicative Compensation for Pattern-of-Life Variations
3.2 Results on Example Social Network Data Set
4 Conclusions
References
Uncovering Latent Influential Patterns and Interests on Twitter Using Contextual Focal Structure Analysis Design
1 Introduction
2 Research Problem Statement
3 Methodology
3.1 Multiplex Matrix Structure
3.2 Data Collection
3.3 CFS Sets Validation and Analysis
3.4 FSA 2.0 vs. CFSA
4 Results and Findings
4.1 Ranking Correlation Coefficient Values (RCC)
4.2 Theoretical Implications
4.3 Practical Implications
5 Conclusion
References
Not My Fault: Studying the Necessity of the User Classification & Employment of Fine-Level User-Based Moderation Interventions in Social Networks
1 Introduction
2 Background
3 Methodology
3.1 Data Collection
3.2 User Classification
4 Results
5 Conclusions
References
Decentralized Networks Growth Analysis: Instance Dynamics on Mastodon
1 Introduction
2 Related Work
2.1 Network Analysis of Mastodon
2.2 User Migration from Twitter to Mastodon
3 Methodology
3.1 Dataset
3.2 Ensuring the Validity of Collected Data
4 Dynamics Analysis and Results
4.1 Account Number Dynamics
4.2 Network-Influence Based on Centrality Metrics
4.3 Community Analysis Using the Louvain Algorithm
4.4 Following Group-Based Analysis
4.5 Analysis of Turkish Accounts
4.6 Individual-Account Instance Analysis
5 Conclusion and Future Work
References
Better Hide Communities: Benchmarking Community Deception Algorithms
1 Introduction
2 Related Work
3 Preliminaries
3.1 Community Deception
3.2 Deception Score
4 Better Hide Communities: A Benchmark for Appraising Community Detection Algorithms
4.1 Networks
4.2 Detection Algorithms
4.3 BHC Benchmark Generation Procedure
4.4 Discussion
5 Conclusion and Future Work
References
Crossbred Method: A New Method for Identifying Influential Spreaders from Directed Networks
1 Introduction
2 Related Work
3 Methodology
4 Experimental Setup
4.1 Datasets
4.2 Benchmark Simulator
4.3 Kendall Rank Correlation Coefficient
5 Experimental Result
6 Conclusion
References
Examining Toxicity's Impact on Reddit Conversations
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Collection
3.2 Data Cleaning and Pre-processing
3.3 Toxicity Detection
3.4 Conversation Tree Generation
3.5 Conversation Tree Visualization
4 Results and Findings
4.1 Conversations End with Toxicity in Different Categories of Tree
4.2 Structure of Toxic Conversations: Wider, Deeper, and Larger Branches
4.3 Predicting the Toxicity of the Last Message in a Reddit Conversation
5 Conclusion and Future Works
References
Analyzing Blogs About Uyghur Discourse Using Topic Induced Hyperlink Network
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Collection
3.2 Topic Modeling
3.3 Toxicity
3.4 Network Analysis
3.5 Morality Analysis
4 Results
4.1 Topic Modeling
4.2 Toxicity Analysis
4.3 Network Analysis
4.4 Morality Analysis
4.5 Network Analysis
5 Conclusion
References
Synchronization
Global Synchronization Measure Applied to Brain Signals Data
1 Introduction
2 Background and Methods
2.1 Preliminaries in Networks
2.2 The Visibility Graph
2.3 Synchronization Dynamic
3 Experimental Results
3.1 Experiment Setup
3.2 Brain Synchronization
4 Conclusions
References
Synchronization Analysis and Verification for Complex Networked Systems Under Directed Topology
1 Introduction
2 Preliminaries
3 Synchronization Analysis and Verification
4 Simulation
5 Conclusion
References
Tolerance-Based Disruption-Tolerant Consensus in Directed Networks
1 Introduction
2 Model Formulation
3 Method: Clusters Consensus Protocol
3.1 Protocol Rules
3.2 Convergence Metric
4 Analysis
5 Results
6 Conclusion
References
Higher-Order Temporal Network Prediction
1 Introduction
2 Network Representation
3 Datasets
4 Network Memory Property
5 Models
5.1 Baseline
5.2 Generalized Model
6 Model Evaluation
6.1 Network Prediction Quality
6.2 Parameter Choice of the Generalized Model
6.3 Performance Analysis
7 Conclusion and Discussion
References
Author Index

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Complex Networks & Their Applications XII

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