Deep Bidirectional LSTM Network Learning-Based Sentiment Analysis for Arabic Text
Sentiment analysis aims to predict sentiment polarities (positive, negative or neutral) of a given piece of text. It lies at the intersection of many fields such as Natural Language Processing (NLP), Computational Linguistics, and Data Mining. Sentiments can be expressed explicitly or implicitly. Ar...
Enregistré dans:
Auteurs principaux: | Elfaik Hanane, Nfaoui El Habib |
---|---|
Format: | article |
Langue: | EN |
Publié: |
De Gruyter
2020
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/fa571cada8a04ec6a4a35e910b9c9132 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Arabic sentiment analysis about online learning to mitigate covid-19
par: Ali Manal Mostafa
Publié: (2021) -
Improving sentiment analysis in Arabic: A combined approach
par: Belgacem Brahimi, et autres
Publié: (2021) -
BengSentiLex and BengSwearLex: creating lexicons for sentiment analysis and profanity detection in low-resource Bengali language
par: Salim Sazzed
Publié: (2021) -
Deep Learning-based Sentiment Analysis and Topic Modeling on Tourism During Covid-19 Pandemic
par: Ram Krishn Mishra, et autres
Publié: (2021) -
Improving Accuracy using The ASERLU layer in CNN-BiLSTM Architecture on Sentiment Analysis
par: Sandi Hermawan, et autres
Publié: (2021)