Improving Arabic Sentiment Analysis Using LSTM Based on Word Embedding Models

Improving Arabic Sentiment Analysis Using LSTM Based on Word Embedding Models

In recent times, online users freely express their sentiments in different life aspects because of the huge increase in social networks. Sentiment Analysis (SA) is one of the main Natural Language Processing (NLP) fields thanks to its important role in identifying sentiment polarities and making dec...

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Bibliographic Details
Main Authors: Youssra Zahidi, Yassine Al-Amrani, Yacine El Younoussi
Format: Article
Language:English
Published: World Scientific Publishing 2023-08-01
Series:Vietnam Journal of Computer Science
Subjects:
Arabic sentiment analysis (ASA)
deep learning (DL)
long short-term memory (LSTM)
word embedding
FastText and Word2Vec
Online Access:https://www.worldscientific.com/doi/10.1142/S2196888823500069

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