This work presents a different approach to sarcasm detection using a publicly accessible dataset from the Kaggle which was carefully selected from news headlines. The collection combines actual headlines from the news from HuffPost with satirical headlines from TheOnion. This dataset's unique features ...
is_sarcastic: 1 if the record is sarcastic otherwise 0 headline: the headline of the news article article_link: link to the original news article. Useful in collecting supplementary data 简介 以前在Sarcasm Detection中进行的研究大多使用Twitter数据集,该数据集是基于基于标签的监督收集的,但这些数据集在...
Researchers often combine the various approaches to improve sarcasm detection. For instance, Signhaniya et al., 2015, Vijayalaksmi and Senthilrajan, 2017 combined lexical, hyperbole and pragmatic approaches to detect sarcasm using bag of words with the latter also focusing on positive sentiment in a...
rishabhmisra/News-Headlines-Dataset-For-Sarcasm-Detection Star87 High quality dataset for the task of Sarcasm Detection nlpdeep-learningsarcasm-detection UpdatedFeb 18, 2023 This repo contains code to detect sarcasm from text in discussion forum using deep learning ...
Evaluation on five benchmark datasets, including English (news headlines, Ghosh Tweet, Riloff Tweet), Hindi, and multilingual Hindi-English (Hinglish), demonstrates the superior performance of CNN-H. The model surpasses various state-of-the-art conventional machine-learning and deep-learning models,...
"Modelling Context with User Embeddings for Sarcasm Detection in Social Media" is authored by Silvio Amir and others from the University of Lisbon and University of Texas at Austin. Research on sarcasm recognition made headlines earlier on, with a report about scientists working on a system capable...
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Bridging the gap in sarcasm detection of the Arabic language is the target behind this work. In this paper, efficient models in short text classification are tested for detecting sarcasm in the Arabic news headlines for the first time. The dataset used to train and test these different ...
Deep learning approaches have proven to be effective in sarcasm detection. In this work, we propose a novel two-stage model that uses a word-embedding technique to select relevant features followed by an advanced deep-learning architecture to classify sarcasm in news headlines...
With the advent of false and manipulative news and the popularity of humorous articles, detecting sarcasm in news articles has turned out to be crucial. In this paper, we evaluated various vectorization and machine learning models to detect sarcastic headlines. Our experiments show that pre-trained...