A Multi-relational Graph-Based Twitter Account Detection Benchmark

The page lists recent research developments in the area of Stance Learning.

Multi-dataset stance detection and robustness experiments

Official resource of the paper "Knowledge Enhanced Masked Language Model for Stance Detection", NAACL 2021

Final project for NLP(DATA130006) in Fudan university.

Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training

A curated list of awesome sentiment analysis studies, in which attitude corresponds to the text position conveyed by Subject towards other Object mentioned in text such as: entities, events, etc.

🧠 NLP笔记，入门概念，基础知识，研究方法，顶会研读

MoLE: Cross-Domain Label-Adaptive Stance Detection

Detection of two phases (swing and stance) phase from the IMU datasets.

A transformer-based language model trained on politics-related Twitter data. This repo is the official resource of the paper "PoliBERTweet: A Pre-trained Language Model for Analyzing Political Content on Twitter", LREC 2022

Code and data for EMNLP '17 paper "Human Centered NLP with User-Factor Adaptation"

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.

Dataset associated with the "Stance Prediction for Contemporary Issues: Data and Experiments" SocialNLP@ACL2020 paper

Implicit Stance Prediction on Political Debates using Speech Features

an approach based on deep ensemble learning

[DASFAA2023] Adversarial Learning-based Stance Classifier for COVID-19-related Health Policies (code&data)

The PyTorch codebase for the NAACL 2021 paper - "tWT–WT: A Dataset to Assert the Role of Target Entities for Detecting Stance of Tweets"

Stance and Gender Detection in Tweets on Catalan Independence

The Pytorch code for baselines and dataset accompanying the NAACL 2021 paper - "tWT–WT: A Dataset to Assert the Role of Target Entities for Detecting Stance of Tweets"