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Preface; New Age ofßWeb Usage; Learn, in Simple Words, Theory and Practice of Social Network Analysis; Contents; Chapter 1: Theoretical Concepts ofßNetwork Analysis; 1.1 Sociological Meaning ofßNetwork 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 andßMutuality; 1.2.6 Balance andßTriads; 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 andßShortest Path1.3.8 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 inßNetwork 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 aßNetwork?; 2.2 Types ofßNetworks; 2.3 Properties ofßNetworks; 2.4 Network Measures.
2.5 NetworkX2.6 Installation; 2.7 Matrices; 2.8 Types ofßMatrices inßSocial 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 ofßGraph Theory; 3.2 Graph Basics; 3.3 Vertices; 3.4 Types ofßGraphs; 3.5 Graph Traversals; 3.5.1 Depth-First Traversal (DFS); 3.5.2 Breadth-First Traversal (BFS); 3.5.3 Dijkstra's Algorithm; 3.6 Operations onßGraphs; Reference; Chapter 4: Social Networks; 4.1 Social Networks.
4.2 Properties ofßaßSocial Network4.2.1 Scale-Free Networks; 4.2.2 Small-World Networks; 4.2.3 Network Navigation; 4.2.4 Dunbar's Number; 4.3 Data Collection inßSocial Networks; 4.4 Six Degrees ofßSeparation; 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 ofßSocial 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 inßtheßNetwork5.2.1 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 toßUse?; 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.
1.3.7 Geodesic Distance andßShortest Path1.3.8 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 inßNetwork 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 aßNetwork?; 2.2 Types ofßNetworks; 2.3 Properties ofßNetworks; 2.4 Network Measures.
2.5 NetworkX2.6 Installation; 2.7 Matrices; 2.8 Types ofßMatrices inßSocial 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 ofßGraph Theory; 3.2 Graph Basics; 3.3 Vertices; 3.4 Types ofßGraphs; 3.5 Graph Traversals; 3.5.1 Depth-First Traversal (DFS); 3.5.2 Breadth-First Traversal (BFS); 3.5.3 Dijkstra's Algorithm; 3.6 Operations onßGraphs; Reference; Chapter 4: Social Networks; 4.1 Social Networks.
4.2 Properties ofßaßSocial Network4.2.1 Scale-Free Networks; 4.2.2 Small-World Networks; 4.2.3 Network Navigation; 4.2.4 Dunbar's Number; 4.3 Data Collection inßSocial Networks; 4.4 Six Degrees ofßSeparation; 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 ofßSocial 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 inßtheßNetwork5.2.1 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 toßUse?; 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.