Filters








453 Hits in 4.4 sec

An Embedding-based Approach for Irony Detection in Arabic tweets

Leila Moudjari, Karima Akli-Astouati
2019 Forum for Information Retrieval Evaluation  
In this paper, we present our results for the IDAT2019 Task: Irony Detection in Arabic Tweets. For this task, labeled data of Arabic tweets was shared.  ...  Sometimes they express their disagreement in a sentence using sarcasm or irony. Irony represents an interesting way for opinion communication towards a particular target in social media.  ...  The IDAT task: Irony Detection in Arabic Texts, focuses on irony detection over a collection of Arabic tweets collected and annotated.  ... 
dblp:conf/fire/MoudjariA19 fatcat:4br2a3tabjflbezebldresn3ju

SSN_NLP@IDAT-FIRE-2019: Irony Detection in Arabic Tweets using Deep Learning and Features-based Approaches

S. Kayalvizhi, D. Thenmozhi, B. Senthil Kumar, Chandrabose Aravindan
2019 Forum for Information Retrieval Evaluation  
We presented three approaches namely deep learning using transformers, deep learning using Recurrent Neural Networks (RNN) and a features-based approach for detecting the irony in Arabic tweets.  ...  The disparity between the statement and its intended meaning is referred to as irony. Detecting this disparity in Arabic tweets is a challenging task.  ...  Acknowledgement We would like to thank the Science and Engineering Research Board (SERB), Department of Science and Technology for funding the GPU system (EEQ/2018/000262) where this work is being carried  ... 
dblp:conf/fire/KayalvizhiTKA19 fatcat:4rjpbb4g75a4dpro3mip4j3tvy

Irony Detection in a Multilingual Context [article]

Bilal Ghanem, Jihen Karoui, Farah Benamara, Paolo Rosso, Véronique Moriceau
2020 arXiv   pre-print
of annotated data for irony.  ...  We show that these monolingual models trained separately on different languages using multilingual word representation or text-based features can open the door to irony detection in languages that lack  ...  A new freely available corpus of Arabic tweets manually annotated for irony detection 4 . II.  ... 
arXiv:2002.02427v1 fatcat:k35g2wtmzrcv7jiiteblyyss6i

IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets

Bilal Ghanem, Jihen Karoui, Farah Benamara, Véronique Moriceau, Paolo Rosso
2019 Forum for Information Retrieval Evaluation  
This overview paper describes the first shared task on irony detection for the Arabic language.  ...  Tweets in our dataset are written in Modern Standard Arabic but also in different Arabic language varieties including Egypt, Gulf, Levantine and Maghrebi dialects.  ...  As far as we know, the sole effort towards Arabic irony detection was done by Karoui et al. [17] who proposed a supervised approach to detecting ironic tweets.  ... 
dblp:conf/fire/GhanemKBMR19a fatcat:mjum7syeznalbnnfqzivucg6ny

Emotion based voted classifier for Arabic irony tweet identification

Nikita Kanwar, Rajesh Kumar Mundotiya, Megha Agarwal, Chandradeep Singh
2019 Forum for Information Retrieval Evaluation  
In this paper, we have worked on irony detection in the Arabic language, a task which is organized by FIRE 2019.  ...  The tweets have been preprocessed and tokenized to extract the frequency-based, emotion-based features. These features are used to irony identification using the voted classifier.  ...  In previous work of irony detection on English: A rule-based approach depends on the hashtag [12] and linguistic features (exclamations and intensifiers) [16] are used.  ... 
dblp:conf/fire/KanwarMAS19 fatcat:midmh33zs5fv5npqyohdf2zhrm

Irony Detection in a Multilingual Context [chapter]

Bilal Ghanem, Jihen Karoui, Farah Benamara, Paolo Rosso, Véronique Moriceau
2020 Lecture Notes in Computer Science  
of annotated data for irony.  ...  We show that these monolingual models trained separately on different languages using multilingual word representation or text-based features can open the door to irony detection in languages that lack  ...  A new freely available corpus of Arabic tweets manually annotated for irony detection 1 . II.  ... 
doi:10.1007/978-3-030-45442-5_18 fatcat:ehfa3t6q3fgcxj4qxhrpggyrv4

Neural Network Approach for Irony Detection from Arabic Text on Social Media

Ali Allaith, Muhammad Shahbaz, Mohammed Alkoli
2019 Forum for Information Retrieval Evaluation  
We also propose a classification system for detecting irony in the Arabic tweets using neural networks 1 .  ...  Humans manipulate each other in a very negative way by writing the opposite of what they mean. However, irony detection is a complex task even for humans.  ...  An Arabic research in irony detection has been proposed in [13] . The proposed system is called "Soukhria".  ... 
dblp:conf/fire/AllaithSA19 fatcat:k2cyit23urarnh25ckn4hjxzji

Detecting Irony in Arabic Microblogs using Deep Convolutional Neural Networks

Linah Alhaidari, Khaled Alyoubi, Fahd Alotaibi
2022 International Journal of Advanced Computer Science and Applications  
This paper explores how deep learning methods can be employed to the detection of irony in Arabic language with the help of Word2vec term representations that converts words to vectors.  ...  In Natural Language Processing (NLP), irony recognition is an important yet difficult problem to solve.  ...  In this paper, we presented an approach based on pre-trained word embedding called AraVec, to address the problem of detecting irony in Arabic tweets.  ... 
doi:10.14569/ijacsa.2022.0130187 fatcat:4xyn7ejmfjauzcldr4vlg2lm4y

RGCL at IDAT: Deep Learning models for Irony Detection in Arabic Language

Tharindu Ranasinghe, Hadeel Saadany, Alistair Plum, Salim Mandhari, Emad Mohamed, Constantin Orasan, Ruslan Mitkov
2019 Forum for Information Retrieval Evaluation  
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 highest F1 score achieved for one of the submissions was 0.818 making the team RGCL rank 4th out of 10 teams in final results.  ...  SemEval-2018 Task 3 focused on irony detection in English tweets [7] . Also, there were shared tasks for irony detection in French [1] and Italian [3] .  ... 
dblp:conf/fire/RanasingheSPMMO19 fatcat:bm76ryhfmzg5zjfwmxe74kv33a

BENHA@IDAT: Improving Irony Detection in Arabic Tweets using Ensemble Approach

Hamada A. Nayel, Walaa Medhat, Metwally Rashad
2019 Forum for Information Retrieval Evaluation  
This paper describes the methods and experiments that have been used in the development of our model submitted to Irony Detection for Arabic Tweets shared task.  ...  Our submissions achieved accuracies of 82.1%, 81.6% and 81.1% for ensemble based, SVM and linear classifiers respectively.  ...  Arabic tweets irony detection has been addressed in [7] , by designing a binary classifier based system for irony detection in Arabic tweets.  ... 
dblp:conf/fire/NayelMR19 fatcat:7hzmftqrhnhkdefurgzpnvnqsi

Overview of the WANLP 2021 Shared Task on Sarcasm and Sentiment Detection in Arabic

Ibrahim Abu Farha, Wajdi Zaghouani, Walid Magdy
2021 Workshop on Arabic Natural Language Processing  
This paper provides an overview of the WANLP 2021 shared task on sarcasm and sentiment detection in Arabic.  ...  The dataset used in this shared task, namely ArSarcasm-v2, consists of 15,548 tweets labelled for sarcasm, sentiment and dialect. We received 27 and 22 submissions for subtasks 1 and 2 respectively.  ...  The work on Arabic sarcasm detection is limited to a few works. soukhria2017 were the first to work on Arabic sarcasm/irony detection.  ... 
dblp:conf/wanlp/FarhaZM21 fatcat:2zttmpkfuzavtg3bxogks6ikoq

sarcasm detection and quantification in arabic tweets [article]

Bashar Talafha, Muhy Eddin Za'ter, Samer Suleiman, Mahmoud Al-Ayyoub, Mohammed N. Al-Kabi
2021 arXiv   pre-print
This paper intends to create a new humanly annotated Arabic corpus for sarcasm detection collected from tweets, and implementing a new approach for sarcasm detection and quantification in Arabic tweets  ...  tweets, and it is considered as a way for people to express their sentiment about some certain topics or issues.  ...  the accuracy of sarcasm/irony detection for Arabic language [18, 19, 20, 21, 22] .  ... 
arXiv:2108.01425v1 fatcat:pxh3grcojrgxhcdirrado5ie64

WANLP 2021 Shared-Task: Towards Irony and Sentiment Detection in Arabic Tweets using Multi-headed-LSTM-CNN-GRU and MaRBERT

Reem Abdel-Salam
2021 Workshop on Arabic Natural Language Processing  
Irony and Sentiment detection is important to understand people's behavior and thoughts. Thus it has become a popular task in natural language processing (NLP).  ...  This paper presents results and main findings in WANLP 2021 shared tasks one and two. The task was based on the ArSarcasm-v2 dataset (Abu Farha et al., 2021) .  ...  The sixth workshop for Arabic Natural Language Processing co-located with EACL 2021, had two shared tasks: Sarcasm and Sentiment Detection in Arabic tweets.  ... 
dblp:conf/wanlp/Abdel-Salam21 fatcat:pkbcaijpwnclxioocmeuexjy3a

Plumeria at SemEval-2022 Task 6: Robust Approaches for Sarcasm Detection for English and Arabic Using Transformers and Data Augmentation [article]

Shubham Kumar Nigam, Mosab Shaheen
2022 arXiv   pre-print
For detecting sarcasm, we used deep learning techniques based on transformers due to its success in the field of Natural Language Processing (NLP) without the need for feature engineering.  ...  This paper describes our submission to SemEval-2022 Task 6 on sarcasm detection and its five subtasks for English and Arabic.  ...  Irony: tweets that contradict the state of affairs but are not obviously critical towards an addressee. 3.  ... 
arXiv:2203.04111v1 fatcat:nvf4vkyfvvfcvpgqaih3yztqna

Deep Multi-Task Model for Sarcasm Detection and Sentiment Analysis in Arabic Language [article]

Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, Nabil El Mamoun, Ismail Berrada, Ahmed Khoumsi
2021 arXiv   pre-print
The prominence of figurative language devices, such as sarcasm and irony, poses serious challenges for Arabic Sentiment Analysis (SA).  ...  While previous research works tackle SA and sarcasm detection separately, this paper introduces an end-to-end deep Multi-Task Learning (MTL) model, allowing knowledge interaction between the two tasks.  ...  Abbes et al. (2020) have built a corpus for irony and sarcasm detection in Arabic language from twitter using a set of ironic hashtags.  ... 
arXiv:2106.12488v1 fatcat:jwzb4e3dabfhhdyrjlzn7zqcza
« Previous Showing results 1 — 15 out of 453 results