  Deep learning techniques have proven their effectiveness for Sentiment
Analysis (SA) related tasks. Recurrent neural networks (RNN), especially Long
Short-Term Memory (LSTM) and Bidirectional LSTM, have become a reference for
building accurate predictive models. However, the models complexity and the
number of hyperparameters to configure raises several questions related to
their stability. In this paper, we present various LSTM models and their key
parameters, and we perform experiments to test the stability of these models in
the context of Sentiment Analysis.
