Stance Detection
106 papers with code • 20 benchmarks • 31 datasets
Stance detection is the extraction of a subject's reaction to a claim made by a primary actor. It is a core part of a set of approaches to fake news assessment.
Example:
- Source: "Apples are the most delicious fruit in existence"
- Reply: "Obviously not, because that is a reuben from Katz's"
- Stance: deny
Benchmarks
These leaderboards are used to track progress in Stance Detection
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Libraries
Use these libraries to find Stance Detection models and implementationsDatasets
LIAR
ARC (AI2 Reasoning Challenge)
Snopes
FNC-1
VAST
COVID-CQ
Subtasks
Most implemented papers
Your Stance is Exposed! Analysing Possible Factors for Stance Detection on Social Media
Results show that stance of a user can be detected with multiple signals of user's online activity, including their posts on the topic, the network they interact with or follow, the websites they visit, and the content they like.
Incorporating Label Dependencies in Multilabel Stance Detection
willferreira/multilabel-stance-detection
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IJCNLP 2019
We propose a method that explicitly incorporates label dependencies in the training objective and compare it against a variety of baselines, as well as a reduction of multilabel to multiclass learning.
Stance Detection Benchmark: How Robust Is Your Stance Detection?
UKPLab/mdl-stance-robustness
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Stance Detection (StD) aims to detect an author's stance towards a certain topic or claim and has become a key component in applications like fake news detection, claim validation, and argument search.
X-Stance: A Multilingual Multi-Target Dataset for Stance Detection
Unlike stance detection models that have specific target issues, we use the dataset to train a single model on all the issues.
Multilingual Stance Detection: The Catalonia Independence Corpus
The TW-10 Referendum Dataset released at IberEval 2018 is a previous effort to provide multilingual stance-annotated data in Catalan and Spanish.
Aspect-Controlled Neural Argument Generation
UKPLab/controlled-argument-generation
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NAACL 2021
In this work, we train a language model for argument generation that can be controlled on a fine-grained level to generate sentence-level arguments for a given topic, stance, and aspect.
StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
Our system, StackGenVis, assists users in dynamically adapting performance metrics, managing data instances, selecting the most important features for a given data set, choosing a set of top-performant and diverse algorithms, and measuring the predictive performance.
Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey
AmmarRashed/UnsupervisedStanceDetection
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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.
Stance Prediction for Contemporary Issues: Data and Experiments
We investigate whether pre-trained bidirectional transformers with sentiment and emotion information improve stance detection in long discussions of contemporary issues.
Stance Detection in Web and Social Media: A Comparative Study
prajwal1210/Stance-Detection-in-Web-and-Social-Media
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Online forums and social media platforms are increasingly being used to discuss topics of varying polarities where different people take different stances.
