@jdp23, I think you may find this interesting.
With @titi we usually discuss on developing metrics that are less simplistic on quantitative stats and that better reflect the richness of a conversation.
In that sense, I am starting to analyze conversations as networks and I think is a very interesting path!
In the figure I attach, I have represented 4 different conversations as networks and they show different patterns of centralization (being the 2 and 3 more centralized). In addition, I use two metrics of decentralization on the receptor of the message for each connection: Gini (lower being more decentralized) and Shannon (higher being more decentralized).
Conversations:
2: https://paquita.masto.host/@chinicuil/112608071118290319
3: https://cosocial.ca/@evan/112457047627977316
4: https://dair-community.social/@timnitGebru/112854573107016934Metrics taken from: https://medium.com/tap-in-with-taptools/edinburgh-decentralization-index-8e6f46c65daa
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