I am trying to find a good way to calculate the drama indicator of a reddit post programmatically as you can see in the title.
Until now all I can think of compering number of upmarseys and comments. If comments > upmarseys much drama
if comments are equal to upmarseys some drama
if comments < upmarseys there is no idea if there is drama or not
I am also thinking of looking average upmarsey and average comment from one week post history of subreddit, but I didn't try that yet.
One also can try to look dramatic users with dramatic post history. I know that reddit uses this to bust ban evading subs by tagging and stalking problematic users. But this seems too much since we don't have free access to reddit api.
I would love to hear more ideas about this. I want to build a drama watch bot where bot can suggest post that involve some drama.
.webp?h=11 "Nuzzles, pounces on you, UwU, you're so warm!..")
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The drama goes up if there is a lolcow in the thread. Which can be algorithmically hinted at by looking at the number of distinct usernames in the comments vs number of comments. More evidence is when there are users that leave a disproportionate amount of comments that have a back and forth pattern with other users.
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this is a good idea.
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This is not a bad metric tbh π€
Maybe run some supervised learning on the top reddit submission to r/drama to find other leads.
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