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Here is a good general explanation of Bayesian inference.
I think @jayrhacker@kbin.social is suggesting using such techniques to predict "troll" or "not troll" given the posting history/removed comments/etc. My personal thought is that whatever system replaces karma, it should be understandable to the typical user. I think its possible Bayesian inference could be used in developing the system, but the end system should be explainable without it.
Thanks for the link. To anyone that does’t know about Bayesian inference, do check it out!
Now I have an existencial crisis thanks to the video 😂 the funny part is that thats the same thing used to detect spam email…
Spam detectors are pretty opaque by their nature. In contrast, karma is pretty easy to understand: "x number of people upvoted comments or posts from this user". This lets people understand a score even if they don't agree. If a karma replacement behaved like a spam detector, it would probably just annoy people.
Sporting brackets may be a better analogy. They are developed with statistics in mind but are understandable to the average sports fan. I think a karma replacement should have similar properties.
That sounds awesome! You seem to be quite knowledgeable about mathematics. May I ask what is your background?
Computer science. However, statistics is more of a hobby than anything. I am just intrigued by the idea of federated social media in general so I have thought a bit on how I would personally make it work. Perhaps I will make some more in depth blog posts about my ideas at some point.