I’m trying to understand how Recurrent Neural Networks (RNNs), such as LSTM or GRU models or just a simple RNN, handle negation in sentiment analysis. Specifically, I’m curious about how these models manage to correctly interpret sentences where negation changes the sentiment, such as “The movie is not good.”