Irony Detection in Persian Language: A Transfer Learning Approach Using Emoji Prediction

Preni Golazizian, Behnam Sabeti, Seyed Arad Ashrafi Asli, Zahra Majdabadi, Omid Momenzadeh, Reza Fahmi


Abstract
Irony is a linguistic device used to intend an idea while articulating an opposing expression. Many text analytic algorithms used for emotion extraction or sentiment analysis, produce invalid results due to the use of irony. Persian speakers use this device more often due to the language’s nature and some cultural reasons. This phenomenon also appears in social media platforms such as Twitter where users express their opinions using ironic or sarcastic posts. In the current research, which is the first attempt at irony detection in Persian language, emoji prediction is used to build a pretrained model. The model is finetuned utilizing a set of hand labeled tweets with irony tags. A bidirectional LSTM (BiLSTM) network is employed as the basis of our model which is improved by attention mechanism. Additionally, a Persian corpus for irony detection containing 4339 manually-labeled tweets is introduced. Experiments show the proposed approach outperforms the adapted state-of-the-art method tested on Persian dataset with an accuracy of 83.1%, and offers a strong baseline for further research in Persian language.
Anthology ID:
2020.lrec-1.346
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2839–2845
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.346
DOI:
Bibkey:
Cite (ACL):
Preni Golazizian, Behnam Sabeti, Seyed Arad Ashrafi Asli, Zahra Majdabadi, Omid Momenzadeh, and Reza Fahmi. 2020. Irony Detection in Persian Language: A Transfer Learning Approach Using Emoji Prediction. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2839–2845, Marseille, France. European Language Resources Association.
Cite (Informal):
Irony Detection in Persian Language: A Transfer Learning Approach Using Emoji Prediction (Golazizian et al., LREC 2020)
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PDF:
https://aclanthology.org/2020.lrec-1.346.pdf