Ranasinghe, Tharindu and Saadany, Hadeel and Plum, Alistair and Al Mandhari, Salim and Mohamed, Emad and Orasan, Constantin and Mitkov, Ruslan (2019) RGCL at IDAT : deep learning models for irony detection in Arabic language. In: Working Notes of FIRE 2019 - Forum for Information Retrieval Evaluation, Kolkata, India, 12th-15th December, 2019. :. CEUR Workshop Proceedings . CEUR Workshop Proceedings, pp. 416-425.
Full text not available from this repository.Abstract
This article describes the system submitted by the RGCL team to the IDAT 2019 Shared Task: Irony Detection in Arabic Tweets. The system detects irony in Arabic tweets using deep learning. The paper evaluates the performance of several deep learning models, as well as how text cleaning and text pre-processing influence the accuracy of the system. Several runs were submitted. The highest F1 score achieved for one of the submissions was 0.818 making the team RGCL rank 4th out of 10 teams in nal results. Overall, we present a system that uses minimal pre-processing but capable of achieving competitive results.