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Dr. Hamada Ali Mohamed Ali Nayel :: Publications: |
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| Title: | BENHA@IDAT: Improving Irony Detection in Arabic Tweets using Ensemble Approach |
| Authors: | Hamada A. Nayel; Walaa Medhat; Metwally Rashad |
| Year: | 2019 |
| Keywords: | Irony Detection; Arabic NLP; Ensemble Based Classifiers; SVM |
| Journal: | Forum of Information Retrieval Evaluation (FIRE2019) |
| Volume: | Not Available |
| Issue: | Not Available |
| Pages: | Not Available |
| Publisher: | Not Available |
| Local/International: | International |
| Paper Link: | |
| Full paper | Hamada Ali Mohamed Ali Nayel_idat.pdf |
| Supplementary materials | Not Available |
| Abstract: |
This paper describes the methods and experiments that have been used in the development of our model submitted to Irony Detec- tion for Arabic Tweets shared task. We submitted three runs based on our model using Support Vector Machines (SVM), Linear and Ensemble classifiers. Bag-of-Words with range of n-grams model have been used for feature extraction. Our submissions achieved accuracies of 82.1%, 81.6% and 81.1% for ensemble based, SVM and linear classifiers respectively |
