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Mastering Gephi Network Visualization

Book Description

Produce advanced network graphs in Gephi and gain valuable insights into your network datasets

In Detail

Mastering Gephi Network Visualization will take you through an overview of Gephi and network behavior, followed by detailed chapters addressing layouts, filtering, graph statistics, dynamic graphs, and more. You will begin with a concise overview of working with the Gephi interface. You will then see how to create your own graphs and understand the graph layouts to arrange a sample dataset. You will understand the theory behind Dynamic Network Analysis, followed by sample applications on how Gephi can be used to model these networks. You will also learn about the plugins that are most critical for network analysis and graph creation. Finally, you will put together all the previously learned concepts and gain insight on the future state of network graph analysis.

After reading this book and following the examples provided, you will have the confidence and expertise to create your own compelling graphs.

What You Will Learn

  • Familiarize yourself with the Gephi interface

  • Understand the plugins that are most critical for network analysis and graph creation

  • Assess your own network graph needs

  • Examine key network behaviors such as contagion, diffusion, and clustering

  • Effectively display a sample dataset using your own graphs

  • Identify and analyze network patterns

  • Use Gephi's powerful filtering capabilities to improve your graphs

  • Create dynamic graphs with time-based network data

  • Export your graphs for use beyond Gephi

  • Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

    Table of Contents

    1. Mastering Gephi Network Visualization
      1. Table of Contents
      2. Mastering Gephi Network Visualization
      3. Credits
      4. About the Author
      5. Acknowledgments
      6. About the Reviewers
      7. www.PacktPub.com
        1. Support files, eBooks, discount offers, and more
          1. Why subscribe?
          2. Free access for Packt account holders
      8. Preface
        1. What this book covers
        2. What you need for this book
        3. Who this book is for
        4. Conventions
        5. Reader feedback
        6. Customer support
          1. Downloading the color images of this book
          2. Errata
          3. Piracy
          4. Questions
      9. 1. Fundamentals of Complex Networks and Gephi
        1. Graph applications
          1. Collaboration graphs
          2. Who-talks-to-whom graphs
          3. Information linkages
          4. Technological networks
          5. Natural-world networks
        2. A network graph analysis primer
          1. Paths and connectivity
            1. Paths
            2. Cycles
            3. Connectivity
          2. Network structure
            1. Centrality
            2. Components
            3. Giant components and clustering
            4. Homophily
            5. Density
          3. Network behaviors
            1. Contagion and diffusion
            2. Network growth
        3. Overviewing Gephi
        4. Primary windows
          1. Data laboratory
            1. Manual entry
            2. CSV import
            3. Excel import
            4. MySQL import
            5. Graph file import
          2. Graph window
          3. Preview window
        5. Secondary windows – tabs
          1. The filtering tab
          2. The statistics tab
          3. The layouts tab
        6. Essential plugins
          1. Clustering – Chinese Whispers
          2. Data laboratory
            1. Data laboratory helper
          3. Exports
            1. Sigma.js Exporter
            2. Seadragon Web Export
            3. Graph Streaming
            4. ExportToEarth
          4. Generator – the Complex Generators plugin
          5. Layout
            1. The Multipartite layout
            2. The Hiveplot layout
            3. The Concentric layout
            4. The OpenOrd layout
            5. The Circular layout
            6. The Layered layout
            7. The ARF layout
          6. Additional plugins
            1. Link Communities – metrics
            2. Give color to nodes – tools
        7. Summary
      10. 2. A Network Graph Framework
        1. A proposed process flow
          1. Identifying an idea or topic
          2. Determining the final output
          3. Identifying the data sources
          4. Formatting the data for Gephi
          5. Importing data into Gephi
          6. Viewing the initial graph layout
          7. Selecting a layout
          8. Analyzing the graph
          9. Modifying the graph
          10. Exporting the graph
        2. Creating an example graph
          1. Identifying the topic
          2. Finding the data source
          3. Formatting the data for Gephi
          4. Importing the data
          5. Viewing the initial network
          6. Selecting an appropriate layout
            1. The Force Atlas layout
            2. The Fruchterman-Reingold layout
            3. The Radial Axis layout
            4. The Yifan Hu layout
            5. ARF
        3. Analyzing the graph
        4. Modifying the graph
        5. Exporting the graph
        6. Summary
      11. 3. Selecting the Layout
        1. Overviewing the layout types
          1. Force-based layouts
          2. The ARF layout
          3. Force Atlas
          4. Force Atlas 2
          5. Force Atlas 3D
          6. The Fruchterman-Reingold algorithm
          7. The OpenOrd algorithm
          8. The Yifan Hu algorithm
          9. The Yifan Hu Proportional layout
          10. The Yifan Hu multilevel approach
          11. Tree layouts
            1. DAG layout
          12. Circular layouts
            1. The Circular layout
            2. The Concentric layout
            3. The Dual Circle layout
          13. Radial layouts
            1. The Hiveplot layout
            2. The Radial Axis layout
          14. Geographic layouts
            1. The Geo layout
            2. The Maps of Countries layout
          15. Additional layouts
            1. The Isometric layout
            2. The Multipartite layout
            3. The Layered layout
            4. Network Splitter 3D
          16. Additional layout tools
        2. Assessing your graphing needs
          1. Actual example – the Miles Davis network
            1. Analysis goal
            2. Dataset parameters
            3. Network density
            4. Network behaviors
            5. Network display
            6. Temporal elements
            7. Interactivity
        3. Layout strengths and weaknesses
        4. Testing layouts
          1. Testing the ARF layout
          2. The Concentric layout
          3. Testing the Radial Axis layout
        5. Layout selection criteria
        6. Graph aesthetics
          1. Working example of graph aesthetics
        7. Summary
      12. 4. Network Patterns
        1. Contagion and diffusion
          1. Contagion
            1. The SIR model
            2. The SIS model
            3. The SIRS model
          2. Diffusion
        2. Clustering and homophily
          1. Clustering
          2. Homophily
        3. Network growth patterns
        4. Using Gephi generators
        5. Viewing a contagion network
        6. Viewing network diffusion
        7. Network clustering
        8. Identifying homophily
        9. Summary
      13. 5. Working with Filters
        1. The filtering theory
        2. Primary filtering functions in Gephi
          1. Attributes
          2. Edges
          3. Operator
          4. Topology
        3. Using simple filters
          1. Using the Equal filter
            1. Applying the regex function
          2. Filtering edges
          3. Using the Partition filter
          4. Working with the Topology filters
        4. Working with complex filters
          1. Applying multiple filter conditions
          2. Using subfilters
          3. Working with Mask and Intersection conditions
          4. Working with the UNION operator
        5. Summary
      14. 6. Graph Statistics
        1. Overview of graph statistics
          1. Network measures
            1. Diameter
            2. Eccentricity
            3. Graph density
            4. Average path length
            5. Connected components
            6. Erdos number
            7. HITS
            8. Edge betweenness
          2. Centrality measures
            1. Degree centrality (undirected graphs)
            2. In-degree centrality (directed graphs)
            3. Out-degree centrality (directed graphs)
            4. Closeness centrality
            5. Eigenvector centrality
            6. Betweenness centrality
          3. Clustering and neighborhood measures
            1. Clustering coefficient
            2. Number of triangles
            3. Modularity
            4. Link Communities
            5. Neighborhood overlap and embeddedness
        2. Interpreting graph statistics
          1. Interpreting network measures
          2. Interpreting centrality statistics
            1. Degree centrality
            2. In-degree centrality
            3. Out-degree centrality
            4. Closeness centrality
            5. Eigenvector centrality
            6. Betweenness centrality
          3. Interpreting clustering statistics
            1. Interpreting clustering coefficients
            2. Number of triangles
            3. Modularity
            4. Link Communities
            5. Embeddedness
        3. Application of statistical measures
          1. Basic statistical applications
            1. Network statistics
              1. Network diameter
              2. Eccentricity
              3. Graph density
              4. Average path length
              5. Edge betweenness
            2. Centrality statistics
              1. Degree centrality
              2. Closeness centrality
              3. Eigenvector centrality
              4. Betweenness centrality
            3. Clustering statistics
              1. Clustering coefficient
              2. Number of triangles
              3. Modularity
              4. Link Communities
              5. Embeddedness
          2. Filtering using graph statistics
        4. Summary
      15. 7. Segmenting and Partitioning a Graph
        1. Partitioning and clustering options
          1. The Partition tab
          2. The Ranking tab
          3. Manual settings
          4. Chinese Whispers
          5. Markov clustering
        2. Partitioning and clustering examples
          1. Partitioning
          2. Working with the Ranking tab
          3. Using color and size options
          4. Manual graph segmentation
          5. Using the Chinese Whispers plugin
          6. Using the Markov Clustering plugin
        3. Summary
      16. 8. Dynamic Networks
        1. When to use DNA
        2. Topology-based DNA
          1. Generating a dynamic network
            1. Understanding time intervals
            2. Working with timelines
          2. Preparing and importing data for DNA
          3. Implementing and viewing a dynamic network
            1. Creating time intervals in an existing project
            2. Adding time intervals to a new project
              1. Using an existing GEXF file
              2. Adding multiple timeframes
          4. Working with timelines
            1. Applying the timeline
            2. Timelines as filters
        3. Attribute-based DNA
          1. Preparing the data
          2. Implementing and viewing dynamic attribute networks
        4. Creating dynamic GEXF files
        5. Summary
      17. 9. Taking Your Graph Beyond Gephi
        1. Overview of the available tools
          1. Graph file exporters
            1. CSV files
            2. DL files
            3. GDF files
            4. GEXF files
            5. GML files
            6. GraphML files
            7. NET files
            8. VNA files
          2. Image exporters
            1. PNG export
            2. SVG export
              1. Editing an SVG file with Inkscape
            3. PDF export
              1. Editing a PDF file in Inkscape
          3. Web exporters
            1. Seadragon Web Export
            2. Sigma.js Exporter
            3. Loxa Web Site Export
        2. Exporting a web graph
          1. Seadragon
          2. SigmaExporter
          3. Loxa Web Site Export
        3. Summary
      18. 10. Putting It All Together
        1. Using Gephi to understand existing networks
        2. Creating new Gephi projects
          1. Project 1 – Newman NetScience dataset
            1. Exploring the network in Gephi
            2. Deploying the project to the Web
          2. Project 2 – high school network with dynamic edges
            1. Using Gephi to explore the network
            2. Creating the project as a PDF
        3. Anticipating the future of network analysis
        4. Summary
      19. A. Data Sources and Other Web Resources
        1. Data sources
        2. Web resources
        3. Import processes
        4. Bibliography
      20. Index