Gephi

Using Gephi

When jumping into Gephi, I've found the most productive thing was to first use easily accessible and Gephi readable data that you are already familiar with. Network graphs are not exactly the easiest things to make sense of, more often than not they are big amorphous blobs of "spaghetti and meatballs" that don't always tell a meaningful story at first sight. Thus, it's important to be familiar (at least somewhat) with the data you're using. So I recommend, if you have a Facebook, downloading the data of your Facebook friend network. First go to the Facebook search bar and type in "netviz." Agree to the terms and then click "personal network" This should start a download of your facebook network in a gdf file. Then open up Gephi, go to fille>open and select your newly downloaded file.It should appear as a large blob of nodes and edges in your overview screen.

The first thing we'll do to make sense out of this graph is adjust the layout. Go to the bottom left hand corner of your screen where there is a dropdown layout menu and select "Force Atlas 2" and then click "Run." The graph will continue to expand until you stop it, so once it spreads out enough to become manageable, click "stop."

Next, you'll want to go to the right hand pane of the screen under Statistics>Network Overview. Here are various algorithms you can run on your data to make more sense out of them. The first one we'll want is to run "modularity." This algorithmically detects communities in your data. For your facebook friends, you might have a community of family: ie. various family members who are all friends with each other but aren't connected to your other friends. After you run the modularity algorithm, head over to the upper left hand corner of your graph and select partition. Hit the refresh button on the side of the dropdown menu and then, in the dropdown menu select "Modularity Class" and click "Apply." Your graph should now be color coded according to the various communities within your Facebook friends: ie. College friends might be red, family might be blue. etc. 

The next helpful algorithm you will want to run is "Average Degree." This measures, on average, how many connections does a node in your network have? After you run it, in the pop up screen you will see all of your nodes and their various number of connections. Next you should go back to the upper left corner and click on "Ranking." Immediately under "Ranking," click on the half red, half white diamond and then proceed to select "In Degree" or "Out Degree" on the dropdown menu below (because Facebook is an undirected network, it doesn't matter if you choose in or out degree) and click "Apply." Now the nodes on the graph should be sized according to the number of connections they have: ie. the friend of yours that has the most friends in common with you, will be the largest node.

Lastly, in the main graph overview window, go to the bottom click the capital "T" icon. Now, when you hover over your graph, the names of your friends will be displaced over their corresponding nodes.

To share your graph, go to the Preview tab and play with the various layouts it allows you. I prefer "Default curved" for edges and nodes. When you're ready, hit the "export SVG/PDF/PNG" button to create an exportable file. We will cover how to share your graphs interactively online in a later section.

Getting Help

Gephi (and the digital humanities more generally) have a large and very active help network where you can ask and answer questions. Gephi Forums should be the first place you go for help. It features many of the Gephi developers and frequent users. If you're having a problem, chances are, someone else in the forums as had the same issue and can help you out too or else, the Gephi developers frequently make patches and updates that fix certain technical bugs.

The second helpful forum is Digital Humanities Questions and Answers. This is a more general forum than Gephi and questions can range over a broad spectrum of issues within the Digital Humanities, but again, it is comprised of a helpful and active base of digital humanists that are happy to help you solve your problems.

Lastly, if you are on twitter, many very smart digital humanists and Gephi experts are there to help and can answer questions very quickly. Of note @seinecle or Clement Levallois who is a developer for Gephi, is very good with addressing technical issues.