Deep learning approaches for Arabic sentiment analysis

Author:

Mohammed Ammar,Kora RaniaORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems

Reference49 articles.

1. Abdul-Mageed M, Diab MT (2012) Awatif: a multi-genre corpus for modern standard arabic subjectivity and sentiment analysis. In: LREC, vol. 515. Citeseer, pp 3907–3914

2. Abdul-Mageed M, Diab MT, Korayem M (2011) Subjectivity and sentiment analysis of modern standard arabic. In: Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies: short papers, vol 2. Association for Computational Linguistics, pp 587–591

3. Ahmed S, Pasquier M, Qadah G (2013) Key issues in conducting sentiment analysis on Arabic social media text. In: 2013 9th international conference on innovations in information technology (IIT). IEEE, pp 72–77

4. Alayba AM, Palade V, England M, Iqbal R (2017) Arabic language sentiment analysis on health services. In: 2017 1st International workshop on Arabic script analysis and recognition (ASAR). IEEE, pp 114–118

5. Alayba AM, Palade V, England M, Iqbal R (2018) A combined cnn and lstm model for arabic sentiment analysis. In: International cross-domain conference for machine learning and knowledge extraction. Springer, pp 179–191

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