Using Word Embedding and Ensemble Learning for Highly Imbalanced Data Sentiment Analysis in Short Arabic Text

Author:

Al-Azani Sadam,El-Alfy El-Sayed M.

Publisher

Elsevier BV

Subject

General Engineering

Reference32 articles.

1. Altowayan A. Aziz and Lixin Tao. Word embeddings for arabic sentiment analysis. In IEEE International Conference on Big Data.

2. A prototype for a standard arabic sentiment analysis corpus;Al-Kabi;International Arab Journal of Information Technology (IAJIT),2016

3. Bashar Al Shboul, Mahmoud Al-Ayyoub, and Yaser Jararweh. Multi-way sentiment classification of arabic reviews. In Proceedings of the 6th IEEE International Conference on Information and Communication Systems (ICICS), pages 206–211, 2015.

4. Cecilia Ovesdotter Alm, Dan Roth, and Richard Sproat. Emotions from text: machine learning for text-based emotion prediction. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pages 579–586. Association for Computational Linguistics, 2005.

5. Tomas AMikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. Efficient estimation of word representations in vector space. In Proceedings of Workshop at International Conference on Learning Representations, 2013.

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