Arabic Sentiment Analysis Using Deep Learning and Ensemble Methods

Deep Learning Models for Sentiment Analysis in Arabic

In this paper, deep learning framework is proposed for text sentiment classification in Arabic. Four different architectures are explored. Three are based on Deep Belief Networks and Deep Auto Encoders, where the input data model is based on the ordinary Bag-of-Words, with features based on the recently developed Arabic Sentiment Lexicon in combination with other standard lexicon features. The ...

Sentiment analysis: Bayesian Ensemble Learning

Topic Based Sentiment Analysis Using Deep Learning

In this paper , we tackle Sentiment Analysis conditioned on a Topic in Twitter data using Deep Learning . We propose a 2-tier approach : In the first phase we create our own Word Embeddings and see that they do perform better than state-of-the-art embeddings when used with standard classifiers. We then perform inference on these embeddings to learn more about a word with respect to all the topi...

Sentiment Analysis in the Arabic Language Using Machine Learning

Sentiment Analysis in the Arabic Language Using Machine Learning Sentiment analysis has recently become one of the growing areas of research related to natural language processing and machine learning. Much opinion and sentiment about specific topics are available online, which allows several parties such as customers, companies and even governments, to explore these opinions. The first task is...

Are Deep Learning Methods Better for Twitter Sentiment Analysis?

Many applications based on sentiment analysis on social media, such as Twitter, have been developed by researchers. Recently, during the Unites States presidential election of 2016, politicians, including president-elect Donald J. Trump, have been using Twitter as a mean of communicating with the public, drawing tremendous attention to Twitter. It is known that sentiment analysis on tweets stil...