DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-8,Issue-11 ( Nov, 2021 ) | |||||||||
Paper Title |
An Enhanced SVM Based Approach for Sentiment Classification of Arabic Tweets of Different Dialects | |||||||||
Author Name |
Gehad Sayed, Mona Farouk | |||||||||
Affilition |
1Postgraduate student, Computer Engineering Cairo University, Giza, Egypt 2Associate Professor, Computer Engineering Cairo University, Giza, Egypt | |||||||||
Pages |
4-8 | |||||||||
Abstract |
Abstract - Arabic Sentiment Analysis (SA) is one of the most common research fields with many open areas. Few studies apply SA to Arabic dialects. This paper proposes different pre-processing steps and a modified methodology to improve the accuracy using normal Support Vector Machine (SVM) classification. The paper works on two datasets Arabic Sentiment Tweets Dataset (ASTD) and Extended Arabic Tweets Sentiment Dataset (Extended-AATSD) which are publicly available for academic use. The results show that the classification accuracy approaches 86%. Keywords - Arabic, Classification, Sentiment Analysis, Tweets. | |||||||||
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