Complex Networks & Their Applications V

Name: Complex Networks & Their Applications V | Proceedings of the 5th International Workshop on Complex Networks and their Applications (COMPLEX NETWORKS 2016)
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Proceedings of the 5th International Workshop on Complex Networks and their Applications (COMPLEX NETWORKS 2016)

Hocine Cherifi Sabrina Gaito Walter Quattrociocchi Alessandra Sala(Herausgeber*in)

Springer (Verlag)

Erschienen am 25. November 2016

XX, 833 Seiten

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Inhalt

Intro
Preface
Organization & Committees
Contents
Part I Network models
1 A Hypotheses-driven Bayesian Approach for Understanding Edge Formation in Attributed Multigraphs
1 Introduction
2 Background
3 Approach
3.1 Generative Edge Formation Models
3.2 Hypothesis Elicitation
3.3 Computation of the Marginal Likelihood
3.4 Application of the Method and Interpretation of Results
4 Experiments
4.1 Synthetic Attributed Multigraph
4.2 Empirical Attributed Multigraph
5 Related Work
6 Discussion
7 Conclusions
References
2 Generating Scaled Replicas of Real-World Complex Networks
1 Introduction
2 Realistic Replicas
3 The Generation Algorithm
4 Fitting Generative Models to Input Graphs
5 Computational Experiments
6 Conclusion
References
3 Modeling of Data Communication Networks using Dynamic Complex Networks and its Performance Studies
1 Introduction
2 Mathematical model and related work
3 Proposed work
4 Simulation and results
5 Conclusions and Future directions
References
4 Testing for the signature of policy in online communities
1 Introduction
2 Related work
3 Materials and methods
3.1 Empirical data
3.2 Experiment protocol
3.3 Simulation
4 Results
4.1 Goodness-of-fit of the power-law model
4.2 Lower bounds
4.3 Exponents
5 Discussion and conclusion
5.1 Future work
References
5 A Temporal-Causal Network Model for the Relation Between Religion and Human Empathy
1 Introduction
2 Literature Overview
3 The Temporal-Causal Network Model
3.1 Mirror Neurons and Internal Simulation
3.2 Action Ownership States of God and Self
3.3 The God-image
3.4 From Conceptual to Numerical Representation of the Model
4 Simulation Scenario: a Person with Fundamentalist Tendencies
5 Discussion and Conclusion
References
6 Network-Oriented Modeling and Analysis of Dynamics Based on Adaptive Temporal-Causal Networks
1 Introduction
2 Network-Oriented Modeling by Temporal-Causal Networks
3 Modelling Mental Processes by Adaptive Networks
4 Modelling Evolving Social Interactions by Adaptive Networks
5 Mathematical Analysis of Temporal-Causal Network Models
6 Mathematical Analysis for Hebbian Learning
7 Mathematical Analysis for the Homophily Principle
8 Discussion
References
7 What governs a language's lexicon? Determining the organizing principles of phonological neighbourhood networks
1 Introduction
2 Method
2.1 Random lexicons
2.2 Network measures
2.3 Robustness to vertex removal
3 Results
3.1 Overall patterns
3.2 Vertex removal
4 Discussion
5 Conclusion
References
8 Dominance, Deference, and Hierarchy Formation inWikipedia Edit-Networks
1 Introduction
2 Background and related work on hierarchy formation and Wikipedia research
3 Dominance, deference, and third-party dominance
4 Statistical model
5 Results and discussion
6 Conclusion
References
Part II Network Measures
9 Identifying Influential Spreaders by Graph Sampling
1 Introduction
2 Related Work
3 The Rank Degree Method
4 Experimental Analysis
4.1 Methods
4.2 Data and Sampling Setup
4.3 Results
5 Conclusion
References
10 Influential Actors Detection Using Attractiveness Model in Social Media Networks
1 Introduction
2 Related Works
3 Approach
4 Implementation
5 Evaluation
5.1 Evaluation Strategy
5.2 Experimental Results
6 Information Diffusion
6.1 Simulation of attraction processes with time-respecting paths
6.2 Experimental results
7 Conclusion
References
11 Analyzing Multiple Rankings of Influential Nodes in Multiplex Networks
1 Introduction
1.1 Research questions
2 Definitions, data, and methods
2.1 Data sets
2.2 Identification of influential nodes as an MCDM
3 Experimental Results
3.1 Air-transportation network
3.2 Law firm data set
3.3 Tweet network data set
4 Summary
References
12 Preserving Sparsity in Dynamic Network Computations
1 Introduction
2 Background and Notation
3 Sparsification
3.1 A little twist
3.2 On the thresholding parameters
3.3 Cost Comparison
3.4 Comparing top K lists
4 Numerical tests
4.1 Adaptive Scaling
4.2 Centrality Approximation
5 Conclusions
References
13 Flows of Knowledge in Citation Networks
1 Introduction
2 Related works
3 Preliminaries
4 Ascending flow in citation networks
4.1 Ascending flow
4.2 Depth restriction and dynamic graph
5 Experimental results
6 Discussion and conclusion
References
14 Detecting Nestedness in Graphs
1 Introduction
2 The Notion of Nestedness
2.1 Definition of Nestedness
2.2 Detecting and Measuring Nestedness
2.3 Benchmark Graphs
3 Algorithm
4 Robustness Analysis
4.1 Calibration of NESTLON
Conclusion
References
15 Clustering of Paths in Complex Networks
1 Introduction
2 Related Work
3 Similarity Measures for Paths
4 Using the Measures for Clustering Paths
4.1 Data
4.2 Ground Truth and Evaluation of the Results
4.3 Results
5 Conclusion
References
16 Complexity Analysis of Small-World Networks" and Spanning Tree Entropy
1 Introduction
2 Related work
3 The particular case of the Small World Network
G3
having the dimension
3.1 The construction and the structural properties of the Small World Network G3
3.2 Evaluation of the Complexity of the Small World Network G3
having the dimension
4 The general case of the SmallWorld Network
Gk
having the dimension
k
4.1 The construction and the structural properties of the Small World Network Gk
4.2 Evaluation of the Complexity of the Small World Network Gk
Note:
5 The entropy of spanning trees of a class of Small World Networks.
6 Conclusion
References
17 Graph Structure Similarity using Spectral Graph Theory
1 Introduction and Motivation
2 Background
3 Methodology: Eigenvalue Distribution
4 Results and Analysis
4.1 Numerical Experiment Outcomes on Synthetic Networks
4.2 Application to terrorist networks
4.3 Conclusions
References
18 A genetic algorithm-based approach to mapping the diversity of networks sharing a given degree distribution and global clustering
1 Introduction
2 Methods
2.1 Network encoding
2.2 Exploration of the space of possible solutions
3 Results
3.1 Effectiveness of the mapping in terms of space coverage
3.2 Comparison with other methods
4 Discussion
References
19 Within network learning on big graphs using secondary memory-based random walk kernels
1 Introduction
2 Local version of the classical RandomWalk algorithm
3 Local version of the Random walk kernel and Kernelized Score Functions
3.1 Putting together the Average score and the local version of the random walk kernel
3.2 Iterative computation of the kernelized Average Score function with p-step RWK
4 Experimental settings
4.1 Dataset description and performance evaluation
4.2 Results
5 Conclusions
References
20 A Method for Evaluating the Navigability of Recommendation Algorithms
1 Introduction
2 Related Work
3 Evaluation Method
4 Experimental Setup
5 Results
6 Personalized Recommendations
7 Discussion
References
Part III Community Structure
21 A New Decision Technique For Sub-community And Multi-Level Knowledge Extraction In Social Networks
1 Introduction
2 Contribution of this work
3 Methodology and algorithm for the detection
4 From PCA to its Karhunen-Loeve Transform Expansion
5 Building the Decision Variable
6 Validation
6.1 Information about the formation of sub-communities
6.2 Information about the intrinsic behavior inside sub-communities
7 Conclusion
References
22 Vertex-centred Method to Detect Communities in Evolving Networks
1 Introduction
2 Related Works
3 Proposed Approach
3.1 Principles
3.2 Proposed Algorithm: DynLOCNeSs
3.3 Preference Measures
4 Experiments
4.1 Protocol
4.2 Preference Measure Comparison
5 Conclusion and Future Works
References
23 Clustering, Prominence and Social Network Analysis on Incomplete Networks
1 Introduction
2 Related Work
3 Methodology
4 Performance Analysis
5 Conclusion
References
24 Evaluating the community partition quality of a network with a genetic programming approach
1 Introduction
2 Genetic Programming
2.1 Terminal and function sets
2.2 Fitness function
2.3 Control parameters
3 Community structure validation problem
4 Methodology
4.1 Terminal set
4.2 Function set
4.3 Fitness
4.4 Control parameters
5 Conclusion
References
25 A graph-based meta-approach for tag recommendation
1 Introduction
2 Related work
3 Proposed approach
4 Community detection in multiplex networks
5 Experiments
6 Conclusion
References
26 Community detection in visibility networks: an approach to categorize percussive influence on audio musical signals
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Database
3.2 Calculating The Variance Fluctuation Series
3.3 Transforming Variance Fluctuations in Graphs
3.4 Modularity
4 Experimental results
4.1 Variance fluctuations
4.2 Visibility networks generated from variance fluctuation
4.3 Modularity
4.4 Number of communities
4.5 Influence of the randomness in the results
4.6 About sample rate changes
4.7 Looking closely at some Percussive and Symphonic Networks
5 Conclusion and future work
References
27 Can we recognize the next user's mobile community?
1 Introduction
2 Problem statement
3 Data set preprocessing
4 Location Prediction based on mobile communities
4.1 User's communities pattern extraction
4.2 Community related features
4.3 Prediction Model
5 Experiments
5.1 Communities and mobility
5.2 Prediction results
6 Conclusion
References
Part IV Dynamics on Networks
28 Why Amicus Curiae Cosigners Come and Go: A Dynamic Model of Interest Group Networks
1 Interest Group Coalition Strategies
2 Hypotheses of Formation & Dissolution
3 Comparing Static & Dynamic Networks
4 Stochastic Model Results
5 Conclusion
References
29 Contradictory information flow in networks with trust and distrust
1 Introduction
2 Related Work
3
4 Model Design and Implementation
5 Experimental results
5.1 Costs of Trust/Distrust by Network Topology
5.2 Distrust and epistemic attitude
5.3 Trust, Distrust and consensus
6 Conclusions
References
30 The Echo Chamber Effect in Twitter: does community polarization increase?
1 Introduction
2 Data collection
2.1 First phase: snowball sampling
2.2 Omitting users ord edges
2.3 Directionality
2.4 Three datasets
2.5 Data collection for the second phase
3 Experiments
3.1 Edges of real network
3.2 New edges of random case
3.3 Deleted edges of random case
3.4 Biased network
4 Conclusions
Future work
References
31 Semantic Stability in Wikipedia
1 Introduction
2 Technical Approach
2.1 Preliminaries
2.2 Experimental Setup
3 Results and Discussion
4 Related work
5 Conclusion and Future Work
References
32 Coopetition and Cooperosity over Opinion Dynamics
1 Introduction
2 Coopetition and cooperosity
3 PWL form of the opinion dynamics model
4 A sufficient condition for the consensus
5 Numerical results
6 Conclusion
References
33 Effect of Direct Reciprocity on Continuing Prosperity of Social Networking Services
1 Introduction
2 Proposed Model for Social Networking Services
2.1 Reciprocity Reward and Meta-Rewards Games
2.2 Evolution by Genetic Algorithm
3 Experiments and Discussion
3.1 Experimental Setting
3.2 Effect of Reciprocity on Cooperation
3.3 Analysis of Phenomena
3.4 Discussion
4 Conclusion
References
34 Co-evolution of two networks representing different social relations in NetSense
1 Introduction
2 NetSense Data and the Networks
3 Related Work
4 Analysis of Co-Evolution of NetSense Networks
4.1 Does higher communication in behavioral network predict the appearance of edges in the cognitive network?
4.2 Do edges in the cognitive network have stronger links in the behavioral network?
4.3 Do newly formed edges in the cognitive network differ from older edges in terms of communication levels between their nodes?
4.4 How likely does communication dissolve after the corresponding edge disappears in the cognitive network?
4.5 Patterns of communication decay following link dissolution in the cognitive network
4.6 Analysis of asymmetric friendship cognitive edges
5 Conclusion
References
Part V Diffusion, Epidemics and Spreading Processes
35 The spread of ideas in a weighted threshold network
1 Introduction
2 An expanded model
2.1 Initial model
2.2 Improved model
3 Results and Discussion
3.1 Weighted average to speed up computation
4 Conclusion and Future work
References
36 Information Diffusion in Heterogeneous Groups
1 Introduction
2 An Opportunity Model of Information Diffusion
2.1 Consequences of randomly added links
3 Simulated Information Spread
3.1 The Downside to Density
3.2 The Role of Diversity
4 Conclusion
References
37 A Novel Approach to Predict Retweets and Replies Based on Privacy and Complexity-Aware Feature Planes
1 Introduction
2 Related Works
3 Data Set Description
4 Feature Planes
4.1 Profile Plane
4.2 Social Plane
4.3 Activity Plane
4.4 Sentiment Plane
4.5 Global Plane
5 Multi-Classification Prediction Model
5.1 Pre-processing and Training Data Generation
5.2 Prediction Model
6 Results and Discussion
7 Conclusions and Future Work
References
38 Least Squares Method for Diffusion Source Localization in Complex Networks
1 Introduction
2 Definitions and notations
3 Observation model for sparse graphs
4 Diffusion Source localization
4.1 Estimating the source node
5 Experimental results
5.1 The diffusion start time is known
5.2 The diffusion start time is unknown
5.3 Real-world networks
6 Conclusion and Future works
References
39 The effects of local network structure on disease spread in coupled networks
1 Introduction
2 Methodology
2.1 The structure of the system
2.2 description of disease spreading rules
2.3 Differential equation model
3 Results
4 Discussion
References
40 The Accuracy of Mean-Field Approximation for Susceptible-Infected-Susceptible Epidemic Spreading with Heterogeneous Infection Rates
1 Introduction
2 Preliminary
2.1 The N-Intertwined Mean-Field Approximation
2.2 The i.i.d. heterogeneous infection rates
2.3 The correlated heterogeneous infection rates
2.4 The network construction and simulations
3 Effect of the heterogeneous infection rates
3.1 The i.i.d. infection rates
3.2 The correlated infection rate
4 Real-world network
5 Conclusion
References
41 Die-out Probability in SIS Epidemic Processes on Networks
1 Introduction
2 The Prevalence and the Die-out Probability
3 The Die-out Probability: an Accurate Approximation
3.1 Complete Graphs
3.2 General Graphs
3.3 NIMFA: Corrected for Die-out
4 Conclusion
Appendix
References
Part VI Resilience and Control
42 Robustness of Network Controllability to Degree-Based Edge Attacks
1 Introduction
2 Background
2.1 Robustness Metrics for Network Controllability
3 Algorithm
4 Experimental Setup
5 Results
5.1 Free Controls vs Fixed Controls
6 Conclusion
References
43 Use of Random Topics as Practical Control Signals in a Social Network Model
1 Introduction
2 Original Model
3 Control Strategies
4 Simulation Results and Discussion
5 Conclusions
References
44 A Multiplex Approach to Urban Mobility
1 A multiplex model of multi-modal transportation
1.1 Multi-layer networks
1.2 Random walk model of a citizen's movement
2 Mathematical analysis of the model
3 Computational approach
3.1 Existing approach
3.2 Proposed algorithm
4 Experimental evaluation
4.1 Coverage on random graphs
4.2 Coverage and resilience on real data
5 Conclusion
References
Part VII Network Visualization
45 Efficient Genealogical Graph Layout
1 Introduction and Related Methods
2 Layering of Genealogical Graph Nodes
3 Nodes Ordering within Layers
3.1 Undirected spanning tree subgraph selection
3.2 Subtree shape characteristics
3.3 Design of node order within layers
4 Implementation, Experiments, and Discussion
5 Conclusion
References
46 NodeTrix-Multiplex: Visual Analytics of Multiplex SmallWorld Networks
1 Introduction
2 Related Work
3 Focus+Context Approach and Data Model
4 NodeTrix-Multiplex: A Visual Analytic Framework
5 Case-Study of a Multiplex Collaboration Network
6 Conclusions
References
Part VIII Social and Political Networks
47 Structural Patterns of the Occupy Movement on Facebook
1 Introduction
2 Methods
2.1 Data Collection
2.2 Classification of users activity
2.3 Bipartite networks and backbone filter
3 Results and Discussion
3.1 Consumption Patterns
3.2 Activity of Polarized Users
3.3 Backbone of Interaction Patterns
4 Conclusions
References
48 Political Participation in Mexico through Twitter
1 Introduction
2 Methodology
2.1 Survey Data
2.2 Twitter Data
3 Results
4 Conclusion
References
49 Online election campaigning: Identifying political parties using likes and comments
1 Introduction
2 The data
2.1 Collection
2.2 Basic statistics
2.3 Network construction
3 Identifying parties and groups of politicians
4 The Australian Federal election
4.1 Analysis of likes
4.2 Analysis of comments
5 The Malaysian general election
5.1 Analysis of likes
5.2 Analysis of comments
6 Conclusion and future work
References
50 Journalistic Relevance Classification in Social Network Messages: an Exploratory Approach
1 Introduction
2 Related Work 3 Methodology
3.1 Crawling from Social Networks
3.2 Text Fragment Pre-Processing
3.3 Crowdflower Classification
3.4 Sample Summary
4 Exploratory Analysis
5 Surrogate Feature Extraction
5.1 Relation between relevance criteria and surrogate features
5.2 Journalistic Relevance Class
6 Classification Model
7 Conclusion
References
Part IX Networks in Finance and Economics
51 Stock prices prediction via tensor decomposition and links forecast
1 Introduction
2 Materials and methods
3 Results
4 Discussion
References
52 Who buys what, where: Reconstruction of the international trade flows by commodity and industry
1 Introduction
2 Model of Network Reconstruction
2.1 Outline of Network Reconstruction Model
2.2 Maximization of the Configuration Entropy
2.3 Algorithm of Cost Estimation
2.4 Sector-Specific Cost by Commodities
2.5 Sector-Specific Trade by Type of Commodities
3 Trade Data
Symbol Description g0
g1
g2
g3
g4
g5
g6
g7
g8
g9
Symbol Description Symbol Description Symbol Description Symbol Description c1
c2
c3
c4
c5
c6
c7
c8
c9
c10
c11
c12
c13
c14
c15
c16
c17
c18
c19
c20
c21
c22
c23
c24
c25
c26
c27
c28
c29
c30
c31
4 Cost Estimation
4.1 Trade Cost of WIOD
4.2 Trade Cost of NBER-UN
4.3 Estimated Sector-Specific Cost by Type of Commodities
5 Reconstructed Sector-Specific Trade Network by Type of Commodities
5.1 Community Structure in WIOD
5.2 Community Structure in NBER-UN
5.3 Community Structure in Reconstructed Sector-Specific Trade Network by Commodities
6 Summary
References
53 Network of Networks: A Meta-model for Simulated Financial Markets
1 Introduction
2 Literature Reviewer
3 Description of Meta-model for the Financial Market
4 Properties of the Calibrated Network
5 Market Emergence Under Homogeneous Complete Network
6 Conclusion and Future Research
References
7 Appendix A
Part X Biological and Ecological Networks
54 Motif-Based Analysis of Effective Connectivity in Brain Networks
1 Introduction
2 Methods
2.1 Directed Phase Transfer Entropy
2.2 Constructing the Directed Network
2.3 Motif Search
2.4 Motif-Based Clustering Algorithm
3 Results
3.1 Significant 3-Motifs
3.2 Significant 4-Motifs
3.3 Motif-Based Clusters
4 Discussion and Conclusions
Appendix
References
55 Functional Reconstruction of Dyadic and Triadic Subgraphs in Spiking Neural Networks
1 Introduction
2 Network Model
2.1 Neuron Models
2.2 Network Construction
3 Spike Train Analysis
3.1 Higher Order Transfer Entropy
3.2 Thresholding
4 Multiplex Networks
5 Results
5.1 Dyadic Subgraphs
5.2 Triadic Subgraphs
6 Discussion
References
56 Modeling and Extending Ecological Networks Using Land Similarity
1 Introduction
2 Ecological Networks and Graph Models
3 Similarity of Natura 2000 Sites
4 Case Study
5 Analysis of Edge Hit Rates and Complex Network Indices
6 Conclusions and Future Work
References
Part XI Network Analysis
57 A graph-based, semi-supervised, credit card fraud detection system
1 Introduction
2 Background and Notation
2.1 Frauds
2.2 Graphs
3 Related Work
4 The Proposed Model
4.1 Dealing with hubs
4.2 Introducing a time gap
4.3 Including investigators feedback
4.4 Removing merchant scores
5 Experimental comparisons
6 Conclusion
References
58 Modeling City Locations as Complex Networks: An initial study
1 Introduction
2 Network Construction
2.1 Dataset
2.2 Nodes, Edges and Weights
3 Graph Measurements and Analysis
4 Location Ranking and Distances
4.1 Location Ranking
4.2 Location Distances
5 Community Analysis
5.1 Network Community
5.2 Geographical Community
6 Conclusion and Future Work
References
59 An analysis of the Bitcoin users graph: inferring unusual behaviours
1 Introduction
2 Related Work
3 Analyzing Indegree Outliers and Detecting
transactions
3.1 On the Economical Meaning of
transactions
3.2 Chaining
transactions
4 From the case study to generic chains
5 Verifying Conjecture 3.1
6 Conclusions
References
60 Networks with Hierarchical Structure: Applications to the Patent Domain
1 Introduction
1.1 Patent networks
1.2 Similarity measures
2 Comparison of weighted hierarchical sets
2.1 Preliminaries
2.2 Weighted taxonomy trees
2.3 Similarity between weighted hierarchical sets
3 Patent portfolios comparison
3.1 Evolution of patent portfolios
3.2 Networks evolution
4 Conclusion
References
61 Social Connection Dynamics in a Health Promotion Network
1 Introduction
2 Dynamical Social Network Analysis
3 Methods
3.1 Data Set and Data Selection
3.2 Social Network Analysis
4 Results
4.1 Nodes, edges and degree distribution
4.2 Largest component and other components
4.3 Centrality measurements
4.4 Homophily
4.5 Identifying influential participants
5 Conclusions
References
62 Social Networks and Construction of Culture: A Socio-Semantic Analysis of Art Groups
1 Introduction
2 Data
3 Method
3.1 Mapping of the Socio-Semantic Networks
3.2 Operationalization of the Social Network
3.3 Descriptive Statistics
3.4 Extraction of socio-semantic subgraphs
4 Results
5 Conclusion
References
63 Water Supply Network Partitioning Based On Weighted Spectral Clustering
1 Introduction
2 Methodology
3 Case study
4 Conclusion
References
64 Robust optimization of power network operation: storage devices and the role of forecast errors in renewable energies
1 Introduction
2 Motivation
3 Robust optimization framework
3.1 Basic control model
3.2 Storage device model
3.3 Uncertainty model
3.4 Optimization model
3.5 Algorithm
3.6 Adversarial problem for storage device operation
3.7 Adversarial problem for line limit constraints
4 Preliminary computational experiments
5 Conclusions
References
65 An Image Segmentation Algorithm based on Community Detection
1 Introduction
2 Community Detection
2.1 Fast multi-scale detection of communities using stability optimization
2.2 Modularity optimization based on Danon greedy agglomerative method
3 Segmentation algorithms
3.1 Super-pixels
3.2 Construction of the similarity matrix
4 Experiments and results
5 Conclusion
References
66 Erratum to: Identifying Influential Spreaders by Graph Sampling
Erratum to: 6 H. Cherifi et al. (eds.), Complex Networks & Their 7 Applications V, Studies
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