Stance Classification

16 papers with code • 1 benchmarks • 3 datasets

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Most implemented papers

A Retrospective Analysis of the Fake News Challenge Stance Detection Task

hanselowski/athene_system 13 Jun 2018

To date, there is no in-depth analysis paper to critically discuss FNC-1's experimental setup, reproduce the results, and draw conclusions for next-generation stance classification methods.

Simple Open Stance Classification for Rumour Analysis

radpet/fake-news-detector RANLP 2017

Stance classification determines the attitude, or stance, in a (typically short) text.

Stance Prediction for Russian: Data and Analysis

npenzin/rustance 5 Sep 2018

As well as presenting this openly-available dataset, the first of its kind for Russian, the paper presents a baseline for stance prediction in the language.

Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM

seongjinpark-88/RumorEval2019 SEMEVAL 2017

This paper describes team Turing's submission to SemEval 2017 RumourEval: Determining rumour veracity and support for rumours (SemEval 2017 Task 8, Subtask A).

Cross-Target Stance Classification with Self-Attention Networks

nuaaxc/cross_target_stance_classification ACL 2018

In stance classification, the target on which the stance is made defines the boundary of the task, and a classifier is usually trained for prediction on the same target.

A Retrospective Analysis of the Fake News Challenge Stance-Detection Task

UKPLab/coling2018_fake-news-challenge COLING 2018

To date, there is no in-depth analysis paper to critically discuss FNC-1{'}s experimental setup, reproduce the results, and draw conclusions for next-generation stance classification methods.

Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation Structure

dadangewp/SemEval2017-RumourEval 7 Jan 2019

On this line, a new shared task has been proposed at SemEval-2017 (Task 8, SubTask A), which is focused on rumour stance classification in English tweets.

BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers

MFajcik/RumourEval2019 SEMEVAL 2019

This paper describes our system submitted to SemEval 2019 Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours, Subtask A (Gorrell et al., 2019).

Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey

AmmarRashed/UnsupervisedStanceDetection 19 May 2020

On June 24, 2018, Turkey conducted a highly consequential election in which the Turkish people elected their president and parliament in the first election under a new presidential system.

Evidence-based Verification for Real World Information Needs

CambridgeNLIP/verification-real-world-info-needs 1 Apr 2021

Claim verification is the task of predicting the veracity of written statements against evidence.