Then, two recurrent neural network architectures are employed to learn emotion-aware word representations by leveraging noisy, but large training data.
we use Long Short-Term Memory (LSTM) networks (Hochreiter and Schmidhuber, 1997) to capture the semantic information between the words of the text document as well as the emotion information provided in the form of the target label obtained through distant supervision.