Deep Learning Based Techniques for Sentiment Analysis: A Survey
Wael Etaiwi, Dima Suleiman, Arafat Awajan
Abstract
The automated representation of human language using a number of techniques is called Natural Language Processing (NLP). Improvements to NLP applications are important and can be done using a variety of methods, including graphs, deep neural networks, and word embedding. Sentiment classification, which attempts to automatically classify opinionated text as positive, negative, or neutral, is a fundamental activity of sentiment analysis. Sentiment analysis methods focused on deep learning over the past five years are analyzed in this review
Topics & Concepts
Sentiment analysisComputer scienceArtificial intelligenceNatural language processingWord embeddingVariety (cybernetics)Deep learningRepresentation (politics)Word (group theory)EmbeddingMachine learningLinguisticsLawPhilosophyPolitical sciencePoliticsSentiment Analysis and Opinion Mining