[tetrisgm]

The other day, I looked at the trending topics. Top one was "Lesbians". I was wondering if there was some kind of development in politics. Nope.

It was all porn. I was on a call with a friend and he checked from his account too and it was there as well, so this wasn't some kinda A/B test thing. It disappeared after a bit. My point is the algo is a bit wonky.

[numpad0]

Twitter had always been the modern day Playboy mag from Sci-Fi era. So there's Bradbury, Lenna, geopolitics, all bound in one.

The catch is it's a UGC based algorithmic system with instant feedback, which means the fastest adapting contents with most bandwidth absolutely wins, which tends to be, like that.

Does anyone have the solution to this problem anyway? I thought this was always inevitable on WWW.

[tetrisgm]

You’d think one person eyeballing topics and flagging stuff would solve it

[numpad0]

Not with 600m organic global active users. The platform moral compass must align to the performance weighted sum total of its user, rather than the other way around.

Trying to bend the platform morality to suit your idealisms seriously ruin yours over time.

[tetrisgm]

I don't see how seeing the current feed of words and going "not this one" before they go online is difficult. You could literally filter 10 per minute and clean up the misfires