Multimodal Sarcasm Detection Dataset
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Updated
Aug 22, 2024 - OpenEdge ABL
Multimodal Sarcasm Detection Dataset
Sarcasm detection on tweets using neural network
Detecting Sarcasm on Twitter using both traditonal machine learning and deep learning techniques.
This repo contains code to detect sarcasm from text in discussion forum using deep learning
High quality dataset for the task of Sarcasm Detection
detect Sarcasm in a text or document
Sarcasm dataset, 15K tweets, very high quality, both intended & perceived sarcasm, rich context
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
[NeurIPS 2022 Oral (Spotlight)] Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classification
Datasets used for iSarcasmEval shared-task (Task 6 at SemEval 2022)
This repository contains the Arabic sarcasm dataset (ArSarcasm)
Sarcasm Detection for Sentiment Analysis
A deep learning model to detect sarcasm in plain text.
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 …
Code and data used for participation in SemEval-2018 Task 3: "Irony detection in English tweets"
It is the implementation of paper "Multi-Modal Sarcasm Detection in Twitter with Hierarchical Fusion Model"
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.
Code for "Dual-Level Adaptive Incongruity-Enhanced Model for Multimodal Sarcasm Detection".
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.
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