Arabic Sentiment Analysis Using Deep Learning: A Review

被引:0
作者
Hakami, Zainab [1 ]
Alshathri, Muneera
Alqhtani, Nora
Alharthi, Latifah
Alhumoud, Sarah [2 ]
机构
[1] Umm AlQura Univ, Coll Comp & Informat Syst, Mecca, Saudi Arabia
[2] Al Imam Mohammad Ibn Saud Islamic Univ IMSIU, Riyadh, Saudi Arabia
来源
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2019年 / 19卷 / 04期
关键词
Arabic; sentiment analysis; deep learning; CNN; RNN; NN; MACHINE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Social media provides a significant source of public opinions and trends. Recently, the interest in analyzing this publicly available data through sentiment analysis has increased noticeably. The use of deep-learning for sentiment analysis is lately under focus, as it provides a scalable and direct way to analyze text without the need to manually feature-engineer the data. As the work on Arabic sentiment analysis using deep learning is scarce and scattered, this paper presents a systematic review of those studies covering the whole literature, analyzing 19 papers. The review proves a general trend of Arabic sentiment analysis performance improvement with deep learning as opposed to sentiment analysis using machine learning.
引用
收藏
页码:255 / 263
页数:9
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