首页    期刊浏览 2025年06月27日 星期五
登录注册

文章基本信息

  • 标题:Arabic Sentiment Analysis Using Deep Learning: A Review
  • 本地全文:下载
  • 作者:Zainab Hakami ; Muneera Alshathri ; Nora Alqhtani
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2019
  • 卷号:19
  • 期号:4
  • 页码:255-263
  • 出版社:International Journal of Computer Science and Network Security
  • 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.
  • 关键词:Arabic; sentiment analysis; deep learning; CNN; RNN; NN.
国家哲学社会科学文献中心版权所有