An LLM will learn anything that helps it predict, including the emotional state of the writer - that is expected.

If you give an LLM the move sequence of a half-played chess game and ask it to continue as white or black, then it has learnt enough to model the ELO rating of both players and will continue playing at that level. It is not playing to win - it is doing what you expect and predicting as well as it can - it predicts the 1500 ELO player will keep playing at that level, and generates moves accordingly.

An LLM appearing to exhibit an emotion (if we anthropomorphize it and read emotion into it's output) is just predicting as well as it can - if the context calls for sad output, they you'd expect to get sad output and will necessarily find that "we're predicting sadness" detector somewhere internally.

Transformers are the same as they ever were from 10 years ago, other than minor efficiency tweaks like MOE and different attention mechanisms. Training is getting more and more complex, resulting in better and better cargo cult reasoning etc, but the architecture remains the same.