The language model (viewable at https://stackroboflow.com ) scores much higher accuracy predicting the next word on Stack Overflow than other datasets like IMDb.
But on the IMDb dataset this approach led to state of the art sentiment analysis results by pulling out the encoder and adding a custom head whereas on Stack Overflow it didn’t grok anything about the score.
Now all I know is I haven’t seen evidence that they aren’t.
I could see how there could be some element of luck in whether a post gets attention before getting buried. It depends who’s online when it’s posted and whether it piques their interest, and many other random factors that don’t have anything to do with the content of the post like how quickly other posts come in afterwards to bury yours, and how any automated algorithms decide to surface it.