Staff Members - Benha University
BENHA@IDAT: Improving Irony Detection in Arabic Tweets using Ensemble Approach
Forum of Information Retrieval Evaluation (FIRE2019) • 2019
Publication Information
Authors
Hamada A. Nayel; Walaa Medhat; Metwally Rashad
Keywords
Irony Detection; Arabic NLP; Ensemble Based Classifiers; SVM
Journal
Forum of Information Retrieval Evaluation (FIRE2019)
Publisher
Not Available
Volume
Not Available
Issue
Not Available
Pages
Not Available
publication.type
International
Paper Link
Open Link
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