The page lists recent research developments in the area of Stance Learning.
Official resource of the paper "Knowledge Enhanced Masked Language Model for Stance Detection", NAACL 2021
MoLE: Cross-Domain Label-Adaptive Stance Detection
Personal implementation of the ACL 19 paper "Tree LSTMs with Convolution Units to Predict Stance and Rumor Veracity in Social Media Conversations"
This repository contains the annotated dataset, the unigrams, bigrams and trigrams referenced in the paper "The Longest Month: Analyzing the Dynamics of Opinions Regarding COVID-19 Vaccination from Tweets in the Month following the First Vaccine Announcement" published in IEEE Access.
The code and data for the Paper 'Inferring Climate Change Stances from Multimodal Tweets' accepted by the Short Paper track of SIGIR 2024
[ACL 2022] JointCL: A Joint Contrastive Learning Framework for Zero-Shot Stance Detection
Rumour Stance Classification of Tweets
Novel unified representation to solve all the sub-tasks of argumentation mining
A paper & data list of research about stance in NLP
The repository contains the stance detection from twitter data project Code and Documentation
Implementation of multi-task learning (MTL) with different Argument Mining subtasks.
Ideology Detection in the Indian Mass Media
This repository contains the annotated dataset, the unigrams, bigrams and trigrams referenced in the paper "Unmasking People’s Opinions behind Mask Wearing during COVID-19 Pandemic – a Twitter Stance Analysis" submitted to the Symmetry journal.
The first Persian stance detection dataset and model
Implementation of the Kurybayashi et al. text span representation method using LLMs
Toolkit for the paper "Explainable Subjective Stance Classification with SetFit in Political Discourse". The project leverages the SetFit few-shot learning framework, Sentence Transformers architecture, and traditional linguistic ML to enhance explainability in stance classification.
Submission for the Fake News Challenge.
Implemantation of a BERT cascade model
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