A systematic review of machine learning techniques for stance detection and its applications

N Alturayeif, H Luqman, M Ahmed - Neural Computing and Applications, 2023 - Springer
Stance detection is an evolving opinion mining research area motivated by the vast increase
in the variety and volume of user-generated content. In this regard, considerable research …

POLITICS: Pretraining with same-story article comparison for ideology prediction and stance detection

Y Liu, XF Zhang, D Wegsman, N Beauchamp… - ar** a classification schema and validating its training
AL Shea, AKB Omapang, JY Cho, MY Ginsparg… - arxiv preprint arxiv …, 2024 - arxiv.org
Most Americans agree that misinformation, hate speech and harassment are harmful and
inadequately curbed on social media through current moderation practices. In this paper, we …

Debating Europe: A multilingual multi-target stance classification dataset of online debates

V Barriere, A Balahur, B Ravenet - … of the LREC 2022 workshop on …, 2022 - aclanthology.org
We present a new dataset of online debates in English, annotated with stance. The dataset
was scraped from the “Debating Europe” platform, where users exchange opinions over …

Integrating n-gram features into pre-trained model: a novel ensemble model for multi-target stance detection

P Chen, K Ye, X Cui - International conference on artificial neural networks, 2021 - Springer
Multi-target stance detection in tweets aims to detect the stance of given texts towards a
specific target entity. Most existing models on stance detection consider word embedding as …

Neural automated writing evaluation for Korean L2 writing

KT Lim, J Song, J Park - Natural Language Engineering, 2023 - cambridge.org
Although Korean language education is experiencing rapid growth in recent years and
several studies have investigated automated writing evaluation (AWE) systems, AWE for …