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
Creator
Contributor
Subject
Language
eng
Member of
MiAaPQ
Literary form
non fiction
Nature of contents
dictionaries
Series statement
Python for Graph and Network Analysis
Label
Python for Graph and Network Analysis
Publication
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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 ofÂ&#xa0;Web Usage" -- "Learn, in Simple Words, Theory and Practice of Social Network Analysis" -- "Contents" -- "Chapter 1: Theoretical Concepts ofÂ&#xa0;Network Analysis" -- "1.1 Sociological Meaning ofÂ&#xa0;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 andÂ&#xa0;Mutuality" -- "1.2.6 Balance andÂ&#xa0;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 andÂ&#xa0;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 inÂ&#xa0;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 aÂ&#xa0;Network?" -- "2.2 Types ofÂ&#xa0;Networks" -- "2.3 Properties ofÂ&#xa0;Networks" -- "2.4 Network Measures" -- "2.5 NetworkX" -- "2.6 Installation" -- "2.7 Matrices" -- "2.8 Types ofÂ&#xa0;Matrices inÂ&#xa0;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 ofÂ&#xa0;Graph Theory" -- "3.2 Graph Basics" -- "3.3 Vertices" -- "3.4 Types ofÂ&#xa0;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 onÂ&#xa0;Graphs" -- "Reference" -- "Chapter 4: Social Networks" -- "4.1 Social Networks" -- "4.2 Properties ofÂ&#xa0;aÂ&#xa0;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 inÂ&#xa0;Social Networks" -- "4.4 Six Degrees ofÂ&#xa0;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 ofÂ&#xa0;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 inÂ&#xa0;theÂ&#xa0;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 toÂ&#xa0;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 inÂ&#xa0;Social Networks" -- "8.1 Diffusion" -- "8.2 Contagion" -- "8.3 Diffusion ofÂ&#xa0;Innovation" -- "8.4 Adoption ofÂ&#xa0;Innovations" -- "8.5 Diffusion ofÂ&#xa0;Innovation Models" -- "8.6 Two-Step Flow Model" -- "8.7 Social Contagion" -- "8.8 Adoption Rate" -- "8.9 Adoption Categories andÂ&#xa0;Thresholds" -- "8.10 Amount ofÂ&#xa0;Exposure" -- "8.11 Adopters andÂ&#xa0;Adoption" -- "8.12 Critical Mass" -- "8.13 Epidemics" -- "8.14 Epidemic Models" -- "8.15 Deterministic Compartmental Models" -- "8.16 SIR Model" -- "8.17 Properties ofÂ&#xa0;theÂ&#xa0;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 andÂ&#xa0;Writing" -- "References"
Dimensions
unknown
{'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

#### Library Locations

• Folsom Library
110 8th St, Troy, NY, 12180, US
42.729766 -73.682577