Gephi Quick Start
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This is the introduction tutorial. It will guide you to the basic steps of network visualization and manipulation in Gephi.
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Gephi Quick Start
- 1. Tutorial Quick Start * Introduction Gephi Tutorial * * * Import file Visualization Layout Quick Start * Ranking (color) * Metrics Welcome to this introduction tutorial. It will guide you to the basic steps of network * Ranking (size) visualization and manipulation in Gephi. * Layout again * Show labels Gephi version 0.7alpha2 was used to do this tutorial. * Community-detection * Partition Get Gephi * Filter * Preview * Export * Save * Conclusion Last updated March 05th, 2010
- 2. Tutorial Quick Start Open Graph File * Introduction • Download the file LesMiserables.gexf * Import file * Visualization • In the menubar, go to File Menu and Open... * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export Graph Format * Save * Conclusion - GEXF - Tulip TLP - GraphML - CSV - Pajek NET - Compressed ZIP - GDF - GML
- 3. Tutorial Quick Start Import Report * Introduction • When your filed is opened, the report sum up data found and issues. * Import file - Number of nodes * Visualization - Number of edges * Layout - Type of graph * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion • Click on OK to validate and see the graph
- 4. Tutorial Quick Start You should now see a graph * Introduction We imported “Les Miserables” dataset1. Coappearance weighted network of * Import file characters in the novel “Les Miserables” from Victor Hugo. * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save Nodes position is random at first, so you may see a slighty different representation. * Conclusion 1 D. E. Knuth, The Stanford GraphBase: A Platform for Combinatorial Computing, Addison-Wesley, Reading, MA (1993).
- 5. Tutorial Quick Start Graph Visualization * Introduction • Use your mouse to move and scale the visualization * Import file - Zoom: Mouse Wheel * Visualization - Pan: Right Mouse Drag * Layout Zoom * Ranking (color) • Locate the “Edge Thickness” slider on the bottom * Metrics * Ranking (size) * Layout again * Show labels * Community-detection Drag * Partition • If you loose your graph, reset the position * Filter * Preview * Export * Save * Conclusion
- 6. Tutorial Quick Start Layout the graph * Introduction Layout algorithms sets the graph shape, it is the most essential action. * Import file * Visualization • Locate the Layout module, on the left panel. * Layout * Ranking (color) • Choose “Force Atlas” * Metrics * Ranking (size) You can see the layout properties below, leave default values. * Layout again * Show labels * Community-detection • Click on to launch the algorithm * Partition * Filter * Preview * Export * Save * Conclusion Layout algorithms Graphs are usually layouted with “Force-based” algorithms. Their principle is easy, linked nodes attract each other and non-linked nodes are pushed apart.
- 7. Tutorial Quick Start Control the layout * Introduction The purpose of Layout Properties is to let you control the algorithm in order to make a * Import file aesthetically pleasing representation. * Visualization * Layout • Set the “Repulsion strengh” at 10 000 to expand * Ranking (color) the graph. * Metrics * Ranking (size) • Type “Enter” to validate the changed value. * Layout again * Show labels * Community-detection * Partition * Filter * Preview • And now the algorithm. * Export * Save * Conclusion
- 8. Tutorial Quick Start You should now see a layouted graph * Introduction * Import file * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion
- 9. Tutorial Quick Start Ranking (color) * Introduction Ranking module lets you configure node’s color and size. * Import file * Visualization • Locate Ranking module, in the top left. * Layout * Ranking (color) • Choose “Degree” as a rank parameter. * Metrics * Ranking (size) * Layout again * Show labels You should obtain the configuration panel below: * Community-detection * Partition * Filter • Click on to see the result. * Preview * Export * Save * Conclusion
- 10. Tutorial Quick Start Let’s configure colors * Introduction * Import file • Move your mouse over the gradient component. * Visualization * Layout * Ranking (color) * Metrics • Double-click on triangles to configure the color * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save Palette * Conclusion Use palette by right-clicking on the panel.
- 11. Tutorial Quick Start Ranking result table * Introduction You can see rank values by enabling the result table. Valjean has 36 links and is the most * Import file connected node in the network. * Visualization * Layout • Enable table result view at the bottom toolbar * Ranking (color) * Metrics * Ranking (size) • Click again on * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion
- 12. Tutorial Quick Start Metrics * Introduction We will calculate the average path length for the network. It computes the path length for * Import file all possibles pairs of nodes and give information about how nodes are close from each other. * Visualization * Layout * Ranking (color) • Locate the Statistics module on the right panel. * Metrics * Ranking (size) * Layout again * Show labels • Click on near “Average Path Length”. * Community-detection * Partition * Filter * Preview * Export * Save Metrics available * Conclusion - Diameter - Betweeness Centrality - Average Path Length - Closeness Centrality - Clustering Coefficient - Eccentricity - PageRank - Community Detection - HITS (Modularity)
- 13. Tutorial Quick Start Metric settings * Introduction The settings panel immediately appears. * Import file * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion • Select “Directed” and click on OK to compute the metric.
- 14. Tutorial Quick Start Metric result * Introduction When finished, * Import file the metric dis- * Visualization plays its result in * Layout a report * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion
- 15. Tutorial Quick Start Ranking (size) * Introduction Metrics generates general reports but also results for each node. Thus three new values * Import file have been created by the “Average Path Length” algorithm we ran. * Visualization - Betweeness Centrality * Layout - Closeness Centrality * Ranking (color) - Eccentricity * Metrics * Ranking (size) * Layout again * Show labels • Go back to Ranking * Community-detection * Partition • Select “Betweeness Centrality” in the list. * Filter This metrics indicates influencial nodes for highest * Preview value. * Export * Save * Conclusion
- 16. Tutorial Quick Start Ranking (size) * Introduction The node’s size will be set now. Colors remain the “Degree” indicator. * Import file * Visualization • Select the diamond icon in the toolbar for size. * Layout * Ranking (color) • Set a min size at 10 and a max size at 50. * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview • And click on to see the result. * Export * Save * Conclusion
- 17. Tutorial Quick Start You should see a colored and sized graph * Introduction * Import file * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion Color: Degree Size: Betweeness Centrality metric
- 18. Tutorial Quick Start Layout again * Introduction The layout is not completely satisfying, as big nodes can overlap smaller. * Import file * Visualization The “Force Atlas” algorithm has an option to take node size in account when layouting. * Layout * Ranking (color) * Metrics • Go Back to the Layout panel. * Ranking (size) * Layout again • Check the “Adjust by Sizes” option and run again the * Show labels algorithm for short moment. * Community-detection * Partition • You can see nodes are not overlapping anymore. * Filter * Preview * Export * Save * Conclusion
- 19. Tutorial Quick Start Show labels * Introduction Let’s explore the network more in details now that colors and size indicates central * Import file nodes. * Visualization * Layout • Display node labels * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels • Set label size proportional to node size * Community-detection * Partition * Filter * Preview * Export * Save • Set label size with the scale slider * Conclusion
- 20. Tutorial Quick Start Community detection * Introduction The ability to detect and study communities is central in network analysis. We would like * Import file to colorize clusters in our example. * Visualization * Layout Gephi implements the Louvain method1, available from the Statistics panel. * Ranking (color) Click on near the “Modularity” line * Metrics * Ranking (size) * Layout again • Select “Randomize” on the panel. * Show labels * Community-detection * Partition * Filter • Click on OK to launch the detection. * Preview * Export * Save * Conclusion 1 Blondel V, Guillaume J, Lambiotte R, Mech E (2008) Fast unfolding of communities in large net- works. J Stat Mech: Theory Exp 2008:P10008. (http://findcommunities.googlepages.com)
- 21. Tutorial Quick Start Partition * Introduction The community detection algorithm created a “Modularity Class” value for each node. * Import file * Visualization The partition module can use this new data to colorize communities. * Layout * Ranking (color) • Locate the Partition module on the left panel. * Metrics • Immediately click on the “Refresh” button to pop- * Ranking (size) ulate the partition list. * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save How to visualize nodes & edges columns? * Conclusion See columns and values for nodes and edges by looking at the Data Table view. Select Data Laboratory tab and click on “Nodes” to refresh the table.
- 22. Tutorial Quick Start Partition * Introduction • Select “Modularity Class” in the partition list. * Import file * Visualization You can see that 9 communities were found, could * Layout be different for you. A random color has been set for each community identifier. * Ranking (color) * Metrics * Ranking (size) • Click on to colorize nodes. * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export Right-click on the panel to access the Randomize colors action. * Save * Conclusion
- 23. Tutorial Quick Start What the network looks like now * Introduction * Import file * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion
- 24. Tutorial Quick Start Filter * Introduction The last manipulation step is filtering. You create filters that can hide nodes and egdes * Import file on the network. We will create a filter to remove leaves, i.e. nodes with a single edge. * Visualization * Layout • Locate the Filters module on the right panel. * Ranking (color) * Metrics • Select “Degree Range” in the “Topology” category. * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter • Drag it to the Queries, drop it to “Drag filter here”. * Preview * Export * Save * Conclusion Drag
- 25. Tutorial Quick Start Filter * Introduction • Click on “Degree Range” to activate the filter. The parameters panel appears. * Import file * Visualization * Layout * Ranking (color) It shows a range slider and the chart that represents the data, the degree distribution * Metrics here. * Ranking (size) * Layout again • Move the slider to sets its lower bound to 2. * Show labels * Community-detection * Partition • Enable filtering by pushing the button. * Filter * Preview * Export Nodes with a degree inferior to 2 are now hidden. * Save * Conclusion Tip You can edit bounds manually by double-clicking on values.
- 26. Tutorial Quick Start The filtered network * Introduction * Import file * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion That ends the manipulation. We will now preview the rendering and prepare to export.
- 27. Tutorial Quick Start Preview * Introduction • Before exporting your graph as a SVG or PDF file, go to the Preview to: * Import file - See exactly how the graph will look like * Visualization - Put the last touch * Layout * Ranking (color) • Select the “Preview” tab in the banner: * Metrics * Ranking (size) * Layout again * Show labels * Community-detection • Click on Refresh to see the preview * Partition * Filter * Preview * Export * Save * Conclusion Tip If the graph is big, reduce the “Preview ratio” slider to 50% or 25% to display a partial graph.
- 28. Tutorial Quick Start Preview * Introduction • In the Node properties, find “Show Labels” and * Import file enable the option. * Visualization * Layout • Click on * Ranking (color) * Metrics * Ranking (size) * Layout again Preview Settings supports Presets, click on the * Show labels presets list and try different configurations. * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion
- 29. Tutorial Quick Start The Previewed Graph * Introduction * Import file * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion
- 30. Tutorial Quick Start Export as SVG * Introduction From Preview, click on SVG near Export. * Import file * Visualization * Layout * Ranking (color) * Metrics SVG Files are vectorial graphics, like PDF. Images scale smoothly to different sizes and * Ranking (size) can therefore be printed or integrated in high-res presentation. * Layout again * Show labels Transform and manipulate SVG files in Inkscape or Adobe Illustrator. * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion High-resolution screenshots If you prefer hi-resolution PNG screenshots only, look at the icon in the visualization properties bar, located at the bottom of the visualization.
- 31. Tutorial Quick Start Save your project * Introduction Saving your project encapsulates all data and results in a single * Import file session file. * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) If you missed some steps, you can download the session: * Layout again * Show labels LesMiserables.gephi * Community-detection * Partition * Filter * Preview * Export * Save * Conclusion
- 32. Tutorial Quick Start Conclusion * Introduction In this tutorial you learned the basic process to open, visualize, manipulate and render * Import file a network file with Gephi. * Visualization * Layout * Ranking (color) * Metrics * Ranking (size) * Layout again * Show labels * Community-detection * Partition * Filter * Preview Go further: * Export • Gephi Website * Save • Gephi Wiki • Gephi forum * Conclusion