Results 251 to 260 of about 4,967,798 (324)

Stance Detection with Stance-Wise Convolution Network

2020
Stance detection aims at identifying the stance (favor, against or neutral) of a text towards a specific target of opinion. Recently, there is a growing interest in using neural models for stance detection, but there are still some challenges to be solved.
Dechuan Yang, Qiyu Wu 0001, Wei Chen 0021, Tengjiao Wang 0003, Zhen Qiu, Di Liu, Yingbao Cui   +6 more
openaire   +1 more source

LLM-Enhanced Multiple Instance Learning for Joint Rumor and Stance Detection with Social Context Information

ACM Transactions on Intelligent Systems and Technology
The proliferation of misinformation, such as rumors on social media, has drawn significant attention, prompting various expressions of stance among users.
Ruichao Yang, Jing Ma, Wei Gao, Hongzhan Lin   +3 more
semanticscholar   +1 more source

Large Language Models Meet Stance Detection: A Survey of Tasks, Methods, Applications, Challenges and Future Directions

arXiv.org
Stance detection is essential for understanding subjective content across various platforms such as social media, news articles, and online reviews. Recent advances in Large Language Models (LLMs) have revolutionized stance detection by introducing novel
Lata Pangtey, Anukriti Bhatnagar, Shubhi Bansal, Shahid Shafi Dar, Nagendra Kumar   +4 more
semanticscholar   +1 more source

RATSD: Retrieval Augmented Truthfulness Stance Detection from Social Media Posts Toward Factual Claims

North American Chapter of the Association for Computational Linguistics
Social media provides a valuable lens for assessing public perceptions and opinions. This paper focuses on the concept of truthfulness stance, which evaluates whether a textual ut-terance affirms, disputes, or remains neutral or indifferent toward a ...
Zhengyuan Zhu, Zeyu Zhang, Haiqi Zhang, Chengkai Li   +3 more
semanticscholar   +1 more source

Comparative learning based stance agreement detection framework for multi-target stance detection

Engineering Applications of Artificial Intelligence
Yun Zhang, Yijia Zhang
exaly   +2 more sources

Zero-Shot Conversational Stance Detection: Dataset and Approaches

Annual Meeting of the Association for Computational Linguistics
Stance detection, which aims to identify public opinion towards specific targets using social media data, is an important yet challenging task. With the increasing number of online debates among social media users, conversational stance detection has ...
Yuzhe Ding, Kang He, Bobo Li, Limin Zheng, Haijun He, Fei Li, Chong Teng, Dong-Hong Ji   +7 more
semanticscholar   +1 more source

Knowledge-Augmented Interpretable Network for Zero-Shot Stance Detection on Social Media

IEEE Transactions on Computational Social Systems
Stance detection on social media has become increasingly important for understanding public opinions on controversial issues. Existing methods often require large amounts of labeled data to learn target-independent transferable knowledge, which is ...
Bowen Zhang, Daijun Ding, Zhichao Huang, Ang Li, Yangyang Li, Baoquan Zhang, Hutchin Huang   +6 more
semanticscholar   +1 more source

Integrating Emotional Features for Stance Detection Aimed at Social Network Security: A Multi-Task Learning Approach

Electronics
Stance detection seeks to identify the public’s position on a specific topic, providing critical insights for applications such as recommendation systems and rumor detection, which are essential for maintaining a secure social media environment.
Qiumei Pu, Fangli Huang, Fude Li, Jieyao Wei, Shan Jiang   +4 more
semanticscholar   +1 more source

Multi-modal Stance Detection: New Datasets and Model

Annual Meeting of the Association for Computational Linguistics
Stance detection is a challenging task that aims to identify public opinion from social media platforms with respect to specific targets. Previous work on stance detection largely focused on pure texts.
Bin Liang, Ang Li, Jingqian Zhao, Lin Gui, Min Yang, Yue Yu, Kam-Fai Wong, Ruifeng Xu   +7 more
semanticscholar   +1 more source

Exploring Multi-Agent Debate for Zero-Shot Stance Detection: A Novel Approach

Applied Sciences
Zero-shot stance detection aims to identify the stance expressed in social media text aimed at specific targets without relying on annotated data. However, due to insufficient contextual information and the inherent ambiguity of language, this task faces
Junxia Ma, Changjiang Wang, L. Rong, Bo Wang, Yaoli Xu   +4 more
semanticscholar   +1 more source