Add to ORKGDeep 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.Comment: Short note, 3 pages, MoroccoAI Annual Conference 202
Due to the rapid development of technology, social media has become more and more common in human da...
Long short-term memory (LSTM) has transformed both machine learning and neurocomputing fields. Accor...
Sentiment analysis is part of computational research that extracts textual data to obtain positive, ...
Although the traditional recurrent neural network (RNN) model can cover the time information of the ...
Sentiment analysis of written customer reviews is a powerful way to generate knowledge about custome...
Sentiment analysis the procedure of computationally identifying and categorizing evaluations express...
Social media is a rich source of information nowadays. If we look into social media, sentiment analy...
Due to the increasing popularity of posting evaluations, sentiment analysis has grown to be a crucia...
Sentiment analysis has taken on various machine learning approaches in order to optimize accuracy, p...
The emergence of social media platforms, which contributed in activating the patterns of connection ...
Since the turn of the century, as millions of user’s opinions are available on the web, sentiment an...
International audienceDeep learning models such as Convolutional Neural Network (CNN) and Long Short...
The relationship between Facebook posts and the corresponding reaction feature is an interesting sub...
Deep learning techniques produce impressive performance in many natural language processing tasks. H...
Sentiment analysis is a form of machine learning that functions to obtain emotional polarity values ...
Due to the rapid development of technology, social media has become more and more common in human da...
Long short-term memory (LSTM) has transformed both machine learning and neurocomputing fields. Accor...
Sentiment analysis is part of computational research that extracts textual data to obtain positive, ...
Although the traditional recurrent neural network (RNN) model can cover the time information of the ...
Sentiment analysis of written customer reviews is a powerful way to generate knowledge about custome...
Sentiment analysis the procedure of computationally identifying and categorizing evaluations express...
Social media is a rich source of information nowadays. If we look into social media, sentiment analy...
Due to the increasing popularity of posting evaluations, sentiment analysis has grown to be a crucia...
Sentiment analysis has taken on various machine learning approaches in order to optimize accuracy, p...
The emergence of social media platforms, which contributed in activating the patterns of connection ...
Since the turn of the century, as millions of user’s opinions are available on the web, sentiment an...
International audienceDeep learning models such as Convolutional Neural Network (CNN) and Long Short...
The relationship between Facebook posts and the corresponding reaction feature is an interesting sub...
Deep learning techniques produce impressive performance in many natural language processing tasks. H...
Sentiment analysis is a form of machine learning that functions to obtain emotional polarity values ...
Due to the rapid development of technology, social media has become more and more common in human da...
Long short-term memory (LSTM) has transformed both machine learning and neurocomputing fields. Accor...
Sentiment analysis is part of computational research that extracts textual data to obtain positive, ...