Gephi Tutorial Quick Start



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Transcription:

Gephi Tutorial Welcome to this introduction tutorial. It will guide you to the basic steps of network visualization and manipulation in Gephi. Gephi version 0.7alpha2 was used to do this tutorial. Get Gephi Last updated March 05th, 2010

Open Graph File Download the file LesMiserables.gexf In the menubar, go to File Menu and Open... Graph Format - GEXF - GraphML - Pajek NET - GDF - GML - Tulip TLP - CSV - Compressed ZIP

Import Report When your filed is opened, the report sum up data found and issues. - Number of nodes - Number of edges - Type of graph Click on OK to validate and see the graph

You should now see a graph We imported Les Miserables dataset 1. Coappearance weighted network of characters in the novel Les Miserables from Victor Hugo. Nodes position is random at first, so you may see a slighty different representation. 1 D. E. Knuth, The Stanford GraphBase: A Platform for Combinatorial Computing, Addison-Wesley, Reading, MA (1993).

Graph Visualization Use your mouse to move and scale the visualization - Zoom: Mouse Wheel - Pan: Right Mouse Drag Locate the Edge Thickness slider on the bottom If you loose your graph, reset the position Zoom Drag

Layout the graph Layout algorithms sets the graph shape, it is the most essential action. Locate the Layout module, on the left panel. Choose Force Atlas You can see the layout properties below, leave default values. Click on to launch the algorithm 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.

Control the layout The purpose of Layout Properties is to let you control the algorithm in order to make a aesthetically pleasing representation. And now the algorithm. Set the Repulsion strengh at 10 000 to expand the graph. Type Enter to validate the changed value.

You should now see a layouted graph

Ranking (color) Ranking module lets you configure node s color and size. Locate Ranking module, in the top left. Choose Degree as a rank parameter. You should obtain the configuration panel below: Click on to see the result.

Let s configure colors Move your mouse over the gradient component. Double-click on triangles to configure the color Palette Use palette by right-clicking on the panel.

Ranking result table You can see rank values by enabling the result table. Valjean has 36 links and is the most connected node in the network. Enable table result view at the bottom toolbar Click again on

Metrics We will calculate the average path length for the network. It computes the path length for all possibles pairs of nodes and give information about how nodes are close from each other. Locate the Click on Statistics module on the right panel. near Average Path Length. Metrics available - Diameter - Average Path Length - Clustering Coefficient - PageRank - HITS - Betweeness Centrality - Closeness Centrality - Eccentricity - Community Detection (Modularity)

Metric settings The settings panel immediately appears. Select Directed and click on OK to compute the metric.

Metric result When finished, the metric displays its result in a report

Ranking (size) Metrics generates general reports but also results for each node. Thus three new values have been created by the Average Path Length algorithm we ran. - Betweeness Centrality - Closeness Centrality - Eccentricity Go back to Ranking Select Betweeness Centrality in the list. This metrics indicates influencial nodes for highest value.

Ranking (size) The node s size will be set now. Colors remain the Degree indicator. Select the diamond icon in the toolbar for size. Set a min size at 10 and a max size at 50. And click on to see the result.

You should see a colored and sized graph Color: Size: Degree Betweeness Centrality metric

Layout again The layout is not completely satisfying, as big nodes can overlap smaller. The Force Atlas algorithm has an option to take node size in account when layouting. Go Back to the Layout panel. Check the Adjust by Sizes option and run again the algorithm for short moment. You can see nodes are not overlapping anymore.

Show labels Let s explore the network more in details now that colors and size indicates central nodes. Display node labels Set label size proportional to node size Set label size with the scale slider

Community detection The ability to detect and study communities is central in network analysis. We would like to colorize clusters in our example. Gephi implements the Louvain method 1, available from the Click on near the Modularity line Statistics panel. Select Randomize on the panel. Click on OK to launch the detection. 1 Blondel V, Guillaume J, Lambiotte R, Mech E (2008) Fast unfolding of communities in large networks. J Stat Mech: Theory Exp 2008:P10008. (http://findcommunities.googlepages.com)

Partition The community detection algorithm created a Modularity Class value for each node. The partition module can use this new data to colorize communities. Locate the Partition module on the left panel. Immediately click on the Refresh button to populate the partition list. How to visualize nodes & edges columns? 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.

Partition Select Modularity Class in the partition list. You can see that 9 communities were found, could be different for you. A random color has been set for each community identifier. Click on Right-click on the panel to access the Randomize colors action. to colorize nodes.

What the network looks like now

Filter The last manipulation step is filtering. You create filters that can hide nodes and egdes on the network. We will create a filter to remove leaves, i.e. nodes with a single edge. Locate the Filters module on the right panel. Select Degree Range in the Topology category. Drag it to the Queries, drop it to Drag filter here. Drag

Filter Click on Degree Range to activate the filter. The parameters panel appears. It shows a range slider and the chart that represents the data, the degree distribution here. Move the slider to sets its lower bound to 2. Enable filtering by pushing the button. Nodes with a degree inferior to 2 are now hidden. Tip You can edit bounds manually by double-clicking on values.

The filtered network That ends the manipulation. We will now preview the rendering and prepare to export.

Preview Before exporting your graph as a SVG or PDF file, go to the Preview to: - See exactly how the graph will look like - Put the last touch Select the Preview tab in the banner: Click on Refresh to see the preview Tip If the graph is big, reduce the Preview ratio slider to 50% or 25% to display a partial graph.

Preview In the Node properties, find Show Labels and enable the option. Click on Preview Settings supports Presets, click on the presets list and try different configurations.

The Previewed Graph

Export as SVG From Preview, click on SVG near Export. SVG Files are vectorial graphics, like PDF. Images scale smoothly to different sizes and can therefore be printed or integrated in high-res presentation. Transform and manipulate SVG files in Inkscape or Adobe Illustrator. High-resolution screenshots If you prefer hi-resolution PNG screenshots only, look at the bar, located at the bottom of the visualization. icon in the visualization properties

Save your project Saving your project encapsulates all data and results in a single session file. If you missed some steps, you can download the session: LesMiserables.gephi

Conclusion In this tutorial you learned the basic process to open, visualize, manipulate and render a network file with Gephi. Go further: Gephi Website Gephi Wiki Gephi forum