A useful companion view would be a smallworldiness: inbound degree vs frequency. I suspect banana follows people who are more likely to also follow each other than I do. That would explain greater compactification in her graph. So my small world would have lower median indegree
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Reminds of the globular cluster vs open cluster distinction in astronomy. The former are a large number of tightly gravitationally bound old stars, the latter are a small number of loosely bound young stars. https://en.wikipedia.org/wiki/Star_cluster …pic.twitter.com/vF55KoldDY
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The first thing that comes to mind for me is that your network probably has a higher idea heterogeneity. This would naturally lead to a more diffuse network, if it were to be connected via followers.
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how did you make these graphs?
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It should be noted that the spacing between the nodes is a parameter you can vary in the layout algorithm: "scaling". I haven't been using a consistent one for each graph. Graphs need different ones to be presentable. But, you can, I think, draw conclusions based on shape etcpic.twitter.com/pWu1sTCsAk
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Although, if you just wanted to just compare the overviews of each graph, you could use identical parameters for everything -- the layout scaling parameter, the node min/max size (based on in-degree), the label text min/max size (based on in-degree). I think that's everything.
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1 - rabbit 2 - elk 3 - dog 4 - chimp 5 - wombat 6 - possum 7 - hippo
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yours does appear uniquely soupy
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