This repo is the work done for IDAT 2019 Shared Task — Shared Task on detecting irony in Arabic tweets by RGCL
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Updated
Jul 24, 2019 - Python
This repo is the work done for IDAT 2019 Shared Task — Shared Task on detecting irony in Arabic tweets by RGCL
Code used in experiment for CLEF2022's Shared Task: Profiling Irony and Stereotype Spreaders on Twitter (IROSTEREO)
This is the Github repository for SemEval-2018 Task 3
This is the project page of the dataset for the binary and multi-label classification of irony in Bengali Tweets.
Persian Irony Detection, include a Persian dataset, creating a dataset automatically, and finetuning transformer-based language models for the task
Course Project (ELEC 880 @ Queen's University)
Multi-View Sentiment Corpus (EACL 2017): tweets labelled by three annotators with sentiment, emotion, irony, subjectivity and implicitness
Coursework project in NLP. Extraction of Irony from Twitter based sentiment analysis.
Advanced NLP project where we needed to build a Sarcasm/Irony classifier. It has many methods like BiLSTM, Transformers to BERT/ T5 / MPNET finetuning
This repo contains my Bachelor's Thesis at the Departement of Informatics of the Universiy of Athens
Natural Language Processing - Sarcasm Detection
Paper: A Cancel Culture Corpus through the lens of Natural Language Processing
Irony Detection in a Multilingual Context
This repo contains work carried out for SemEval 2022 Task 6: iSarcasmEval: Intended Sarcasm Detection In English and Arabic
Code for 3 papers: 1) "Fuzzy-Rough Nearest Neighbour Approaches for Emotion Detection in Tweets"; 2) "LT3 at SemEval-2022 Task 6: Fuzzy-Rough Nearest neighbor Classification for Sarcasm Detection"; 3) "Fuzzy Rough Nearest Neighbour Methods for Detecting Emotions, Hate Speech and Irony" by O. Kaminska, Ch. Cornelis and V. Hoste.
System for irony detection in product reviews
This repo represents model developed for Irony and sentiment detection in Arabic tweets in WANLP shared tasks on sarcasm and sentiment detection in Arabic tweets
MirasText
Code and data used for participation in SemEval-2018 Task 3: "Irony detection in English tweets"
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