In several recent posts, I’ve been exploring in a rather clumsy and over complicated way how we can use Gephi to look at commenting behaviour around shared photos. In this post, I take a step back to look at a much simpler approach… Just plotting the comment graph…
So for example, take a CSV file along the lines of:
where we use a simple CSV file to denote commenter ID and photo ID, and look at the result as a directed graph.
Here’s the graph with nodes sized by in-degree (large nodes are well commented photos):
And then for nodes sized by out degree (large nodes are people who have commented lots of photos):
Here we colour nodes by the out-degree and size it by in-degree, using colour range boundaries to help us colour the graph:
Using the Autoselect neighbour feature we can look at who commented on a photo:
and then what other photos they commented on:
The ego filter trivially shows us, at depth 1, the photos a person has commented on:
(If the photo nodes were sized according to the number of incoming comments from the original graph, we’d be able to see which popularly commented on photos an individual had commented on)
At ego filter depth 2, we can see who else has commented on the same photos:
Running statistics over the depth 2 ego filter graph and plotting the results would allow us to see which individuals have commented on a large number of the same photos as the ego filtered individual.
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