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The Resource Python for Graph and Network Analysis

Python for Graph and Network Analysis

Label
Python for Graph and Network Analysis
Title
Python for Graph and Network Analysis
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Subject
Language
eng
Member of
Cataloging source
MiAaPQ
Literary form
non fiction
Nature of contents
dictionaries
Series statement
Advanced Information and Knowledge Processing
Python for Graph and Network Analysis
Label
Python for Graph and Network Analysis
Link
http://libproxy.rpi.edu/login?url=https://ebookcentral.proquest.com/lib/rpi/detail.action?docID=4826503
Publication
Copyright
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Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • "Preface" -- "New Age of Web Usage" -- "Learn, in Simple Words, Theory and Practice of Social Network Analysis" -- "Contents" -- "Chapter 1: Theoretical Concepts of Network Analysis" -- "1.1 Sociological Meaning of Network Relations" -- "1.2 Network Measurements" -- "1.2.1 Network Connection" -- "1.2.2 Transitivity" -- "1.2.3 Multiplexity" -- "1.2.4 Homophily" -- "1.2.5 Dyads and Mutuality" -- "1.2.6 Balance and Triads" -- "1.2.7 Reciprocity" -- "1.3 Network Distribution" -- "1.3.1 Distance Between Two Nodes" -- "1.3.2 Degree Centrality" -- "1.3.3 Closeness Centrality" -- "1.3.4 Betweenness Centrality" -- "1.3.5 Eigenvector Centrality" -- "1.3.6 PageRank" -- "1.3.7 Geodesic Distance and Shortest Path" -- "1.3.8 Eccentricity" -- "1.3.9 Density" -- "1.4 Network Segmentation" -- "1.4.1 Cohesive Subgroups" -- "1.4.2 Cliques" -- "1.4.3 K-Cores" -- "1.4.4 Clustering Coefficient" -- "1.4.5 Core/Periphery" -- "1.4.6 Blockmodels" -- "1.4.7 Hierarchical Clustering" -- "1.5 Recent Developments in Network Analysis" -- "1.5.1 Community Detection" -- "1.5.2 Link Prediction" -- "1.5.3 Spatial Networks" -- "1.5.4 Protein-Protein Interaction Networks" -- "1.5.5 Recommendation Systems" -- "1.6 iGraph" -- "Chapter 2: Network Basics" -- "2.1 What Is a Network?" -- "2.2 Types of Networks" -- "2.3 Properties of Networks" -- "2.4 Network Measures" -- "2.5 NetworkX" -- "2.6 Installation" -- "2.7 Matrices" -- "2.8 Types of Matrices in Social Networks" -- "2.8.1 Adjacency Matrix" -- "2.8.2 Edge List Matrix" -- "2.8.3 Adjacency List" -- "2.8.4 Numpy Matrix" -- "2.8.5 Sparse Matrix" -- "2.9 Basic Matrix Operations" -- "2.10 Data Visualization" -- "Chapter 3: Graph Theory" -- "3.1 Origins of Graph Theory" -- "3.2 Graph Basics" -- "3.3 Vertices" -- "3.4 Types of Graphs" -- "3.5 Graph Traversals" -- "3.5.1 Depth-First Traversal (DFS)"
  • "3.5.2 Breadth-First Traversal (BFS)" -- "3.5.3 Dijkstraâ{u0080}{u0099}s Algorithm" -- "3.6 Operations on Graphs" -- "Reference" -- "Chapter 4: Social Networks" -- "4.1 Social Networks" -- "4.2 Properties of a Social Network" -- "4.2.1 Scale-Free Networks" -- "4.2.2 Small-World Networks" -- "4.2.3 Network Navigation" -- "4.2.4 Dunbarâ{u0080}{u0099}s Number" -- "4.3 Data Collection in Social Networks" -- "4.4 Six Degrees of Separation" -- "4.5 Online Social Networks" -- "4.6 Online Social Data Collection" -- "4.7 Data Sampling" -- "4.8 Social Network Analysis" -- "4.9 Social Network Analysis vs. Link Analysis" -- "4.10 Historical Development" -- "4.11 Importance of Social Network Analysis" -- "4.12 Social Network Analysis Modeling Tools" -- "References" -- "Chapter 5: Node-Level Analysis" -- "5.1 Ego-Network Analysis" -- "5.2 Identifying Influential Individuals in the Network" -- "5.2.1 Degree Centrality" -- "5.2.2 Closeness Centrality" -- "5.2.3 Betweenness Centrality" -- "5.2.4 Eigenvector Centrality" -- "5.3 PageRank" -- "5.4 Neighbors" -- "5.5 Bridges" -- "5.6 Which Centrality Algorithm to Use?" -- "Chapter 6: Group-Level Analysis" -- "6.1 Cohesive Subgroups" -- "6.2 Cliques" -- "6.3 Clustering Coefficient" -- "6.4 Triadic Analysis" -- "6.5 Structural Holes" -- "6.6 Brokerage" -- "6.7 Transitivity" -- "6.8 Coreness" -- "6.9 Overlapping Communities" -- "6.10 Dynamic Community Finding" -- "6.11 M-Slice" -- "6.12 K-Cores" -- "6.13 Community Detection" -- "6.13.1 Graph Partitioning" -- "6.13.2 Hierarchical Clustering" -- "6.14 Blockmodels" -- "6.14.1 Modularity Optimization" -- "6.15 The Louvain Method" -- "Reference" -- "Chapter 7: Network-Level Analysis" -- "7.1 Components/Isolates" -- "7.2 Core/Periphery" -- "7.3 Density" -- "7.4 Shortest Path" -- "7.5 Reciprocity" -- "7.6 Affiliation Networks" -- "7.7 Two-Mode Networks" -- "7.8 Homophily"
  • "Chapter 8: Information Diffusion in Social Networks" -- "8.1 Diffusion" -- "8.2 Contagion" -- "8.3 Diffusion of Innovation" -- "8.4 Adoption of Innovations" -- "8.5 Diffusion of Innovation Models" -- "8.6 Two-Step Flow Model" -- "8.7 Social Contagion" -- "8.8 Adoption Rate" -- "8.9 Adoption Categories and Thresholds" -- "8.10 Amount of Exposure" -- "8.11 Adopters and Adoption" -- "8.12 Critical Mass" -- "8.13 Epidemics" -- "8.14 Epidemic Models" -- "8.15 Deterministic Compartmental Models" -- "8.16 SIR Model" -- "8.17 Properties of the SIR Model" -- "Appendices" -- "Appendix A: Python 3.x Quick Syntax Guide" -- " Python Syntax" -- " Variables" -- " Numbers" -- " Strings" -- " Lists" -- " Tuples" -- " Dictionaries" -- " Conditionals" -- " Loops" -- " Python Functions" -- " File Handling" -- " Exception Handling" -- " Modules" -- " Classes" -- "Appendix B: NetworkX Tutorial" -- "Graph Types" -- " Nodes" -- " Edges" -- " Directed Graphs" -- " Attributed Graphs" -- " Weighted Graphs" -- " Multigraphs" -- " Classic Graph Operations" -- " Graph Generators" -- " Basic Network Analysis" -- " Centrality Measures" -- " Drawing Graphs" -- " Algorithms Package (NetworkX Algorithms)" -- " Reading and Writing" -- "References"
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{'f': 'http://opac.lib.rpi.edu/record=b4387724'}
Extent
1 online resource (214 pages)
Form of item
online
Isbn
9783319530048
Media category
computer
Media MARC source
rdamedia
Media type code
c
Sound
unknown sound
Specific material designation
remote

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