Heterogeneous Ensemble Deep Learning Model for Enhanced Arabic Sentiment Analysis
Sentiment analysis was nominated as a hot research topic a decade ago for its increasing importance in analyzing the people’s opinions extracted from social media platforms. Although the Arabic language has a significant share of the content shared across social media platforms, its content’s sentim...
Main Authors: | Hager Saleh, Sherif Mostafa, Abdullah Alharbi, Shaker El-Sappagh, Tamim Alkhalifah |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-05-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/10/3707 |
Similar Items
-
Enhanced Arabic Sentiment Analysis Using a Novel Stacking Ensemble of Hybrid and Deep Learning Models
by: Hager Saleh, et al.
Published: (2022-09-01) -
Ensemble Stacking Model for Sentiment Analysis of Emirati and Arabic Dialects
by: Arwa A. Al Shamsi, et al.
Published: (2023-09-01) -
Surface and Deep Features Ensemble for Sentiment Analysis of Arabic Tweets
by: Nora Al-Twairesh, et al.
Published: (2019-01-01) -
Stacked-CNN-BiLSTM-COVID: an effective stacked ensemble deep learning framework for sentiment analysis of Arabic COVID-19 tweets
by: Naglaa Abdelhady, et al.
Published: (2024-04-01) -
A study of the performance of embedding methods for Arabic short-text sentiment analysis using deep learning approaches
by: Ali Alwehaibi, et al.
Published: (2022-09-01)