Use of large language models for stance classification
IJ Cruickshank, LHX Ng - arXiv preprint arXiv:2309.13734, 2023 - arxiv.org
Stance detection, the task of predicting an author's viewpoint towards a subject of interest,
has long been a focal point of research. Current stance detection methods predominantly …
has long been a focal point of research. Current stance detection methods predominantly …
Political-llm: Large language models in political science
In recent years, large language models (LLMs) have been widely adopted in political
science tasks such as election prediction, sentiment analysis, policy impact assessment, and …
science tasks such as election prediction, sentiment analysis, policy impact assessment, and …
TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings
HWA Hanley, Z Durumeric - arXiv preprint arXiv:2310.14450, 2023 - arxiv.org
Stance detection is important for understanding different attitudes and beliefs on the Internet.
However, given that a passage's stance toward a given topic is often highly dependent on …
However, given that a passage's stance toward a given topic is often highly dependent on …
The risk co-de model: detecting psychosocial processes of risk perception in natural language through machine learning
V Rizzoli - Journal of Computational Social Science, 2024 - Springer
This paper presents a classification system (risk Co-De model) based on a theoretical model
that combines psychosocial processes of risk perception, including denial, moral …
that combines psychosocial processes of risk perception, including denial, moral …
Adversarial contrastive representation training with external knowledge injection for zero-shot stance detection
Zero-shot stance detection (ZSSD) is a task that involves identifying the author's perspective
on specific issues in text, particularly when the target topic has not been encountered during …
on specific issues in text, particularly when the target topic has not been encountered during …
Summarization of Opinionated Political Documents with Varied Perspectives
Global partisan hostility and polarization has increased, and this polarization is heightened
around presidential elections. Models capable of generating accurate summaries of diverse …
around presidential elections. Models capable of generating accurate summaries of diverse …
Target-Phrase Zero-Shot Stance Detection: Where Do We Stand?
D Motyka, M Piasecki - International Conference on Computational …, 2024 - Springer
Stance detection, ie recognition of utterances in favor, against or neutral in relation to some
targets is important for text analysis. However, different approaches were tested on different …
targets is important for text analysis. However, different approaches were tested on different …
Developing a Natural Language Understanding Model to Characterize Cable News Bias
SP Benson, IJ Cruickshank - IEEE Access, 2024 - ieeexplore.ieee.org
Media bias has been extensively studied by both social and computational sciences.
However, current work still has a large reliance on human input and subjective assessment …
However, current work still has a large reliance on human input and subjective assessment …
MGKM at StanceEval2024 Fine-Tuning Large Language Models for Arabic Stance Detection
M Alghaslan, K Almutairy - Proceedings of The Second Arabic …, 2024 - aclanthology.org
Social media platforms have become essential in daily life, enabling users to express their
opinions and stances on various topics. Stance detection, which identifies the viewpoint …
opinions and stances on various topics. Stance detection, which identifies the viewpoint …
Acquired TASTE: Multimodal Stance Detection with Textual and Structural Embeddings
G Barel, O Tsur, D Volenchik - arXiv preprint arXiv:2412.03681, 2024 - arxiv.org
Stance detection plays a pivotal role in enabling an extensive range of downstream
applications, from discourse parsing to tracing the spread of fake news and the denial of …
applications, from discourse parsing to tracing the spread of fake news and the denial of …