Sentiment analysis of Algerian Arabic dialect on social media Using Bi-LSTM recurrent neural networks

Sentiment analysis of Algerian Arabic dialect on social media Using Bi-LSTM recurrent neural networks

This paper presents a sentiment analysis approach using Bidirectional Long Short-Term Memory (Bi-LSTM) Recurrent Neural Networks to train predictive models for sentiment analysis on social media, particularly focusing on Algerian Arabic Dialect. The method leverages word-to-vector embedding for wor...

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Bibliographic Details
Main Authors: Abdelghani BOUZIANE, Benamar BOUOUGADA, Djelloul BOUCHIHA, Noureddine DOUMI
Format: Article
Language:English
Published: Universidade Federal de Viçosa (UFV) 2024-10-01
Series:The Journal of Engineering and Exact Sciences
Subjects:
Sentiment analysis
Artificial intelligence
Social Web evolution
Deep learning solutions
Bi-LSTM
Online Access:https://periodicos.ufv.br/jcec/article/view/20058
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https://periodicos.ufv.br/jcec/article/view/20058

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