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Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
Gephi tutorial: quick start
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Gephi tutorial: quick start

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  • 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

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