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Social Network Analysis for Startups : Finding connections on the social web /
Does your startup rely on social network analysis? This concise guide provides a statistical framework to help you identify social processes hidden among the tons of data now available. Social network analysis (SNA) is a discipline that predates Facebook and Twitter by 30 years. Through expert SNA r...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media,
2011.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Table of Contents; Preface; Prerequisites; Open-Source Tools; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Thanks; Chapter 1. Introduction; Analyzing Relationships to Understand People and Groups; Binary and Valued Relationships; Symmetric and Asymmetric Relationships; Multimode Relationships; From Relationships to Networks--More Than Meets the Eye; Social Networks vs. Link Analysis; The Power of Informal Networks; Terrorists and Revolutionaries: The Power of Social Networks; Social Networks in Prison; Informal Networks in Terrorist Cells.
- The Revolution Will Be TweetedSocial Media and Social Networks; Egyptian Revolution and Twitter; Chapter 2. Graph Theory--A Quick Introduction; What Is a Graph?; Adjacency Matrices; Edge-Lists and Adjacency Lists; 7 Bridges of Königsberg; Graph Traversals and Distances; Depth-First Traversal; Implementation; DFS with NetworkX; Breadth-First Traversal; Algorithm; BFS with NetworkX; Paths and Walks; Dijkstra's Algorithm; Graph Distance; Graph Diameter; Why This Matters; 6 Degrees of Separation is a Myth!; Small World Networks; Chapter 3. Centrality, Power, and Bottlenecks.
- Sample Data: The Russians are Coming!Get Oriented in Python and NetworkX; Read Nodes and Edges from LiveJournal; Snowball Sampling; Saving and Loading a Sample Dataset from a File; Centrality; Who Is More Important in this Network?; Find the "Celebrities"; Degree centrality in the LiveJournal network; Find the Gossipmongers; Find the Communication Bottlenecks and/or Community Bridges; Putting It Together; Who Is a "Gray Cardinal?"; In practice; Klout Score; PageRank--How Google Measures Centrality; Simplified PageRank algorithm; What Can't Centrality Metrics Tell Us?
- Chapter 4. Cliques, Clusters and ComponentsComponents and Subgraphs; Analyzing Components with Python; Islands in the Net; Subgraphs--Ego Networks; Extracting and Visualizing Ego Networks with Python; Triads; Fraternity Study--Tie Stability and Triads; Triads and Terrorists; The "Forbidden Triad" and Structural Holes; Structural Holes and Boundary Spanning; Triads in Politics; Directed Triads; Analyzing Triads in Real Networks; Real Data; Cliques; Detecting Cliques; Hierarchical Clustering; The Algorithm; Clustering Cities; Preparing Data and Clustering; Block Models.
- Triads, Network Density, and ConflictChapter 5. 2-Mode Networks; Does Campaign Finance Influence Elections?; Theory of 2-Mode Networks; Affiliation Networks; Attribute Networks; A Little Math; 2-Mode Networks in Practice; PAC Networks; Candidate Networks; Expanding Multimode Networks; Exercise; Chapter 6. Going Viral! Information Diffusion; Anatomy of a Viral Video; What Did Facebook Do Right?; How Do You Estimate Critical Mass?; Wikinomics of Critical Mass; Content is (Still) King; Heterogenous Preferences; How Does Information Shape Networks (and Vice Versa)?; Birds of a Feather?