Say you’re interested in patterns of communication between individuals who are members of multiple organizations (like for instance historical societies), or artefact types across multiple sites. You might like to map the network between these individuals and those organizations to understand something of how information flows in that world, how social norms permeate, or ideologies of consumption or display map across space (as Tom Brughmans does here and I’ve done in other places).
You’ll need Gephi and Sci2. Download and install these. Registration is required for Sci2. Any work you do with these tools, if published, requires the citation of the tool. Don’t forget!
1. Make a list. Every time you encounter an individual mentioned as a member of a group, write it out. Two columns: Source, Target. Shawn Graham, Carleton University. You might include a third column called ‘weight’ which gives some measure of the importance of that connection. Why ‘source’, why ‘target’? Because we’re going to import that list into Gephi, and that’s how Gephi requires the information. However, when we do any sort of metrics, we’ll always treat this network as undirected; that is, we’re making no claim to know anything about the direction of the relationship (in a directed network, Alice’s connection to Bob is different than Bob’s connection to Alice). Save that list as a .csv file. If you graphed this right now, you’d have a network where there are two kinds of nodes; hence a two-mode network. Network statistics envision a network where the modes are all of the same kind, which is why we’re doing this tutorial.
2. Import the list into Gephi. Open Gephi, start a new project. Click on the ‘data laboratory’ lab. Under ‘data table’ click on ‘edges’ (this is important; if you click on ‘nodes’, this doesn’t work correctly). Click on ‘import spreadsheet’. Select your csv file, and make sure that ‘as table:’ is set to ‘edges table’. Click next. Click Finish.
3. Go to File ->> export ->> graph file. Save as file type .net (Pajek).
4. Open Sci2; click on File >> Load and select your .net file.
5. Click ‘data preparation’ >> extract reference co-occurence (bibliographic coupling) network. (see also 5.b, below under ‘variations’)
6. Click ‘preprocessing’ >> networks >> delete isolates. You’ve now collapsed your two-mode network into a one mode network where your nodes under ‘target’ are now all connected to each other. If your source, target was ‘site’, ‘ware’, you’ve got a one mode network where wares are connected to each other by virtue of being listed at the same site, ie, the linkage implies the site. (If you’ve done step 5.b, your one mode network would be sites connected to each other by virtue of sharing the same wares; the linkage implies the ware.)
7. At this point, go to file >> view and your notepad application will open, displaying a table where each node in your network has its own unique id, and ‘label*string’, which is your original label. You’ll Save this from notepad as a txt file. You might call it ‘ware to ware index’ (following our example in 6).
8.This is where things get a bit tricky. Click ‘File’ >> ‘save’. Select ‘pajek .net’ as your file type.(see also 8.b below, under ‘variations’)
9. You can then go back to Gephi, start a new project, click ‘open’ and select the .net file you just created. Your one mode network will load up. HOWEVER Gephi won’t recognize the original node lables anymore. This is why you need the index you saved in step 7, so that when you run metrics on this one mode network, you’ll know that ‘node 342 is actually Stamped Brick CIL XV.1 841.d (for instance). (see also 9.b below, under ‘variations’)
Variations
5.b In step 5, you created a one mode network based on your ‘target’ column. To create a one mode network based on your ‘source’ column, click ‘data preparation’ >> extract document co-citation network. Resume at step 6.
8.b If you want to preserve the node labels in Gephi, instead of step 8.a, click on Visualization >> Networks >> GUESS. This is a small visualization tool (that allows you to do some network metrics; but if your network is v. big, > 1000 nodes, this might not be a good idea). In GUESS, click File >> export graph. Give it a file name that makes sense, and don’t forget to type in the extension .gdf; otherwise it won’t export. Go to step 9b.
9.b Go to Gephi, start a new project, click on ‘open’, and select the .gdf file you just created. Your node labels will now be present in the graph, and so you don’t need that index file you created. Perhaps a bug: In my experiments, node labels don’t seem to appear in the ‘graph overview’ pane, when working with the gdf file. Your experience might be different. However, they do appear when I export an image of the network, under ‘preview’ >> export.
Fin. Let me know if/how your experience differs, or if these steps require clarification.
