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Constructing and evaluating ArabicStanceX: a social media dataset for Arabic stance detection [PDF]

open access: yesFrontiers in Artificial Intelligence
Arabic stance detection has attracted significant interest due to the growing importance of social media in shaping public opinion. However, the lack of comprehensive datasets has limited research progress in Arabic Natural Language Processing (NLP).
Ali Alkhathlan   +3 more
doaj   +3 more sources

Collaborative Knowledge Infusion for Low-Resource Stance Detection [PDF]

open access: yesBig Data Mining and Analytics
Stance detection is the view towards a specific target by a given context (e.g. tweets, commercial reviews). Target-related knowledge is often needed to assist stance detection models in understanding the target well and making detection correctly ...
Ming Yan   +2 more
doaj   +4 more sources

Zero-shot stance detection: Paradigms and challenges [PDF]

open access: yesFrontiers in Artificial Intelligence, 2023
A major challenge in stance detection is the large (potentially infinite) and diverse set of stance topics. Collecting data for such a set is unrealistic due to both the expense of annotation and the continuous creation of new real-world topics (e.g., a ...
Emily Allaway, Kathleen McKeown
doaj   +2 more sources

Zero-shot cross-lingual stance detection via adversarial language adaptation [PDF]

open access: yesPeerJ Computer Science
Stance detection has been widely studied as the task of determining if a social media post is positive, negative or neutral towards a specific issue, such as support towards vaccines.
Bharathi A., Arkaitz Zubiaga
doaj   +3 more sources

Enhancing zero-shot stance detection via multi-task fine-tuning with debate data and knowledge augmentation

open access: yesComplex & Intelligent Systems
In the real world, stance detection tasks often involve assessing the stance or attitude of a given text toward new, unseen targets, a task known as zero-shot stance detection.
Qinlong Fan   +4 more
doaj   +2 more sources

Social context in political stance detection: Impact and extrapolation. [PDF]

open access: yesPLoS ONE
Stance detection is an important task with a wide range of high-impact social applications, including opinion polling and detecting propaganda, misinformation, and hate speech. In this work, we explore the performance and extrapolation power of political
Ramon Villa-Cox   +2 more
doaj   +2 more sources

LOGIC: LLM-originated guidance for internal cognitive improvement of small language models in stance detection [PDF]

open access: yesPeerJ Computer Science
Stance detection is a critical task in natural language processing that determines an author’s viewpoint toward a specific target, playing a pivotal role in social science research and various applications.
Woojin Lee, Jaewook Lee, Harksoo Kim
doaj   +3 more sources

Enhancing Zero-Shot Stance Detection with Contrastive and Prompt Learning. [PDF]

open access: yesEntropy (Basel)
In social networks, the occurrence of unexpected events rapidly catalyzes the widespread dissemination and further evolution of network public opinion.
Yao Z, Yang W, Wei F.
europepmc   +2 more sources

Integrating Graph Neural Networks and Large Language Models for Stance Detection via Heterogeneous Stance Networks

open access: yesApplied Sciences
Stance detection, the task of identifying the stance expressed in a text toward a specific target, is essential for analyzing public opinion across diverse domains. The existing approaches primarily focus on modeling the semantic relationship between the
Xinyi Chen   +5 more
doaj   +2 more sources

Evaluating automatic annotation of lexicon-based models for stance detection of M-pox tweets from May 1st to Sep 5th, 2022. [PDF]

open access: yesPLOS Digital Health
Manually labeling data for supervised learning is time and energy consuming; therefore, lexicon-based models such as VADER and TextBlob are used to automatically label data.
Nicholas Perikli   +10 more
doaj   +2 more sources

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