Results 251 to 260 of about 4,714,839 (322)

Sarcasm Detection with Commonsense Knowledge

IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021
Sarcasm is commonly used in today's social media platforms such as Twitter and Reddit. Sarcasm detection is necessary for analysing people's real sentiments as people usually use sarcasm to express a flipped emotion against the literal meaning. However, the current works neglect the fact that commonsense knowledge is crucial for sarcasm recognition. In
Jiangnan Li, Hongliang Pan, Zheng Lin 0001, Peng Fu 0008, Weiping Wang 0005   +4 more
openaire   +1 more source

Sarcasm Detection in Newspaper Headlines

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS), 2020
Sarcasm is an important part of communication, and detecting sarcasm is difficult for humans, let alone computers. Newspapers often seem to employ sarcasm in their headlines to grab the readers’ attention. However, more often than not, the readers find it difficult to detect the irony in the headlines, thus getting a wrong idea about that particular ...
Parnavi Shrikhande, Vikram Setty, Ashish Kumar Sahani   +2 more
openaire   +1 more source

Enhancing Sarcasm Detection Using GAN-BERT with Multi-Task Learning

2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN)
Sarcasm detection remains a complex task in natural language processing due to its nuanced and contextdependent nature. This paper introduces a novel sarcasm detection framework combining GAN-BERT and Multitask Learning (MTL), where sentiment and emotion
Afif Hossain Irfan, Shrabani Das, Jannatul Ferdaus, Md. Tabil Ahammed   +3 more
semanticscholar   +1 more source

Elevating Knowledge-Enhanced Entity and Relationship Understanding for Sarcasm Detection

IEEE Transactions on Knowledge and Data Engineering
Sarcasm thrives on popular social media platforms such as Twitter and Reddit, where users frequently employ it to convey emotions in an ironic or satirical manner.
Xiaobao Wang, Yujing Wang, Dongxiao He, Zhe Yu, Yawen Li, Longbiao Wang, Jianwu Dang, Di Jin   +7 more
semanticscholar   +1 more source

Multi-modal Sarcasm Detection on Social Media via Multi-Granularity Information Fusion

ACM Trans. Multim. Comput. Commun. Appl.
The rising popularity of diverse social media platforms, commonly utilized by individuals to articulate their emotions in everyday interactions, has spurred a growing interest in the task of multi-modal sarcasm detection (MSD).
Lisong Ou, Zhixin Li
semanticscholar   +1 more source

Detecting Sarcasm in Text

2019
Sarcasm is a nuanced form of speech extensively employed in various online platforms such as social networks, micro-blogs etc. and sarcasm detection refers to predicting whether the text is sarcastic or not. Detecting sarcasm in text is among the major issues facing sentiment analysis.
Sakshi Thakur, Sarbjeet Singh, Makhan Singh   +2 more
openaire   +1 more source

Affective Representations for Sarcasm Detection

The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018
Sarcasm detection from text has gained increasing attention. While one thread of research has emphasized the importance of affective content in sarcasm detection, another avenue of research has explored the effectiveness of word representations. In this paper, we introduce a novel model for automated sarcasm detection in text, called Affective Word ...
Ameeta Agrawal, Aijun An
openaire   +1 more source

Intra-modal Relation and Emotional Incongruity Learning using Graph Attention Networks for Multimodal Sarcasm Detection

IEEE International Conference on Acoustics, Speech, and Signal Processing
Sarcasm detection poses unique challenges due to the complex nature of sarcastic expressions often embedded across multiple modalities. Current methods frequently fall short in capturing the incongruent emotional cues that are essential for identifying ...
Devraj Raghuvanshi, Xiyuan Gao, Zhu Li, Shubhi Bansal, Matt Coler, Nagendra Kumar, Shekhar Nayak   +6 more
semanticscholar   +1 more source

Enhancing Semantic Awareness by Sentimental Constraint With Automatic Outlier Masking for Multimodal Sarcasm Detection

IEEE transactions on multimedia
Multimodal sarcasm detection, aiming to uncover sarcastic sentiment behind multimodal data, has gained substantial attention in multimodal communities. Recent advancements in multimodal sarcasm detection (MSD) methods have primarily focused on modality ...
Shaozu Yuan, Yiwei Wei, Hengyang Zhou, Qinfu Xu, Meng Chen, Xiaodong He   +5 more
semanticscholar   +1 more source

Multi-Modal Sarcasm Detection via Knowledge-Aware Focused Graph Convolutional Networks

ACM Trans. Multim. Comput. Commun. Appl.
Multi-Modal Sarcasm Detection (MSD) aims to combine multiple modal information to identify implicit sarcastic sentiment. However, the significance of commonsense knowledge in implicit emotion recognition has been frequently overlooked.
Xingjie Zhuang, Fengling Zhou, Zhixin Li
semanticscholar   +1 more source