Model Arabic Sentiment Analysis Using Different Machine learning Algorithms in Hotels Domains

Authors

  • Yousra Faisal Gad Sudan University of Since and Technology

Keywords:

Sentiment analysis, Arabic language, Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Recurrent Neural Networks (RNN)

Abstract

With the popularity of Social Medias, sentiment analysis turns into the most important technique for understanding the opinion of users toward products or services. Arabic users are writing their comments using unstructured non-grammatical colloquial Arabic language, which made a complex challenge for sentiment analysis to operate without doing a lot of cleaning preprocessing stage. In this respect, this paper proposes a model on Arabic sentiment analysis with different classification algorithms using manual Arabic lexicon in hotels domain. Our experiment shows Logistic Regression and Support Vector Machine has the highest accuracy with 89% than other classifiers.

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Published

2019-09-27

How to Cite

Gad, Y. F. (2019). Model Arabic Sentiment Analysis Using Different Machine learning Algorithms in Hotels Domains. International Journal of Engineering Technology and Computer Research, 7(5). Retrieved from https://ijetcr.org/index.php/ijetcr/article/view/509

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Section

Articles