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

LSTM based models stability in the context of Sentiment Analysis for social media