Nice.

How do you determine this?

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Any duplicated message with > 50 chars and exactly the same content gets marked as Spam.

If they are made by the same user and the user is not a follow of the current user, mark user as spammer.

Spammer goes into a timeout filter until the app goes to the background and back, when the process and counter restarts.

Nice.

Just thinking out loud, not knowing your exact approach, one method one could compare note content by percentage is to write a function that adds up all the ASCII characters in a note and then produce a score from this. Notes with over 50 characters and with small score differentials posted within a short timeframe are thereby similar in content and likely spam.

And there are tons of text similarity algorithms. No idea which one will work better.

Right. The real spam problems will surface further on when AI bots will make procedurally generated content. Then web-of-trust scores may become useful.

This is a great feature! âš¡

Looking forward to updating my amethyst app.