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Graph Analysis and Visualization: Discovering Business Opportunity in Linked Data

Book Description

Wring more out of the data with a scientific approach to analysis

Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book.

Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers.

  • Study graphical examples of networks using clear and insightful visualizations

  • Analyze specifically-curated, easy-to-use data sets from various industries

  • Learn the software tools and programming languages that extract insights from data

  • Code examples using the popular Python programming language

  • There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences - until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.

    Table of Contents

    1. Titlepage
    2. Copyright
    3. Dedication
    4. About the Authors
    5. About the Technical Editors
    6. Introduction
      1. Who This Book Is For
      2. How This Book Is Structured
      3. Materials for Download
      4. What You Need to TRY THE EXAMPLES
      5. Caveats
      6. Conventions
    7. Part 1: Overview
      1. Chapter 1: Why Graphs?
        1. Visualization in Business
        2. Graphs in Business
        3. Graphs Today
        4. Summary
      2. Chapter 2: A Graph for Every Problem
        1. Relationships
        2. Hierarchies
        3. Communities
        4. Flows
        5. Spatial Networks
        6. Summary
    8. Part 2: Process and Tools
      1. Chapter 3: Data—Collect, Clean, and Connect
        1. Know the Objective
        2. Collect: Identify Data
        3. Clean: Fix the Data
        4. Connect: Organize Graph Data
        5. Putting It All Together
        6. Summary
      2. Chapter 4: Stats and Layout
        1. Basic Graph Statistics
        2. Layouts
        3. Putting It All Together
        4. Summary
      3. Chapter 5: Visual Attributes
        1. Essential Visual Attributes
        2. Key Node Attributes
        3. Key Edge Attributes
        4. Combining Basic Attributes
        5. Bundles, Shapes, Images, and More
        6. Putting It All Together
        7. Summary
      4. Chapter 6: Explore and Explain
        1. Explore, Explain, and Export
        2. Essential Exploratory Interactions
        3. More Interactive Exploration
        4. Explain
        5. Putting It All Together
        6. Summary
      5. Chapter 7: Point-and-Click Graph Tools
        1. Excel
        2. NodeXL
        3. Gephi
        4. Cytoscape
        5. yEd
        6. Summary
      6. Chapter 8: Lightweight Programming
        1. Python
        2. JavaScript and Graph Visualization
        3. Summary
    9. Part 3: Visual Analysis of Graphs
      1. Chapter 9: Relationships
        1. Links and Relationships
        2. E-mail Relationships
        3. Actors and Movies
        4. Links Turned into Nodes
        5. Summary
      2. Chapter 10: Hierarchies
        1. Organizational Charts
        2. Trees and Graphs
        3. Drawing a Hierarchy
        4. Decision Trees
        5. Website Trees and Effectiveness
        6. Summary
      3. Chapter 11: Communities
        1. What Defines a Community?
        2. Graph Clustering
        3. Cliques and Other Groups
        4. Summary
      4. Chapter 12: Flows
        1. Sankey Diagrams
        2. Constructing a Sankey Diagram
        3. Community Layouts with Flow
        4. Chord Diagrams
        5. Constructing a Chord Diagram
        6. Behavioral Factor Tree
        7. Summary
      5. Chapter 13: Spatial Networks
        1. Schematic Layout
        2. Small World Grouping
        3. Link Rose Summaries
        4. Route Patterns
        5. Summary
    10. Part 4: Advanced Techniques
      1. Chapter 14: Big Data
        1. Graph Databases
        2. Graph Query Languages
        3. Analyzing Neighborhoods
        4. Plotting Network Activity
        5. Community Visualization
        6. Summary
      2. Chapter 15: Dynamic Graphs
        1. Graph Changes
        2. Transaction Graphs
        3. Summary
      3. Chapter 16: Design
        1. Nodes
        2. Links
        3. Color
        4. Summary
    11. Glossary
    12. End-User License Agreement