Popular GitHub Repositories for Sarcasm

State-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.

?A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc

Sarcasm detection on tweets using neural network

Detecting Sarcasm on Twitter using both traditonal machine learning and deep learning techniques.

[NeurIPS 2022 Oral (Spotlight)] Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classification

This is a Text Analysis App which can be used to find a detailed analysis of a particular text. This includes 5 main types of Analysis - Spam/Ham Detection, Sentiment Analysis, Stress Detection, Hate & Offensive Content Detection, Sarcasm Detection

Code for "Dual-Level Adaptive Incongruity-Enhanced Model for Multimodal Sarcasm Detection".

Sarcasm Detection for Sentiment Analysis

A deep learning model to detect sarcasm in plain text.

Code and data used for participation in SemEval-2018 Task 3: "Irony detection in English tweets"

Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 on sarcasm detection are presented in this paper.

The Multimodal Sarcasm Detection System detects sarcasm in multimedia content using image-caption generation and NLP. It achieved 1st place in UITC2024 by classifying sarcasm into four categories: image, text, multi sarcasm, and not sarcasm.

A sarcasm detection model using Bidirectional Encoder Representations for Transformers (BERT) and Graph Convolutional Networks (GCN) has shown state-of-art results against conventional models and vanilla transformer-based approaches.

Official repository of the paper "InterCLIP-MEP: Interactive CLIP and Memory-Enhanced Predictor for Multi-modal Sarcasm Detection"

ArSarcasm-v2 is an extension to the original ArSarcasm dataset. It was used for the shared task on sarcasm detection and sentiment analysis, which is a part of WANLP 2021.

Shared task of the Second Workshop on Figurative Language Processing, co-located with ACL 2020

Code-switching patterns can be an effective route to improve performance of downstream NLP applications: A case study of humour, sarcasm and hate speech detection

Sarcasm Detection using LSTM, GRU, and RoBERTa on SARC (reddit), sarcasm_v2, and iSARCASM (twitter) datasets

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.

A TensorFlow project to detect sarcasm in tweets using the power of GloVe embeddings and Convolution layers.