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Stance Detection datasets
archive 2025-07-2835 datasets carry the task tag "Stance Detection" (the task itself: Stance Detection), ordered by the archive's paper count. Page 1 of 1: 35 shown of 35. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
All 12,172
Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52Stance Detection 35
Stance Detection datasets 1–35 of 35
The AI2’s Reasoning Challenge (ARC) dataset is a multiple-choice question-answering dataset, containing questions from science exams from grade 3 to grade 9.
178 papers · 3 benchmarks
LIAR is a publicly available dataset for fake news detection.
130 papers · 1 benchmark
P-Stance: A Large Dataset for Stance Detection in Political Domain 2021
32 papers · 1 benchmark
Fact-checking (FC) articles which contains pairs (multimodal tweet and a FC-article) from snopes.com.
22 papers · 1 benchmark
FNC-1 (Fake News Challenge Stage 1)
FNC-1 was designed as a stance detection dataset and it contains 75,385 labeled headline and article pairs.
19 papers · 2 benchmarks
VAST (VAried Stance Topics)
VAST consists of a large range of topics covering broad themes, such as politics (e.g., ‘a Palestinian state’), education (e.g., ‘charter schools’), and public health (e.g., ‘childhood vaccination’).
18 papers · 1 benchmark
A large-scale stance detection dataset from comments written by candidates of elections in Switzerland.
16 papers · 0 benchmarks
Perspectrum is a dataset of claims, perspectives and evidence, making use of online debate websites to create the initial data collection, and augmenting it using search engines in order to expand and diversify the dataset.
11 papers · 1 benchmark
MGTAB (Multi-Relational Graph-Based Twitter Account Detection Benchmark)
MGTAB is the first standardized graph-based benchmark for stance and bot detection.
10 papers · 2 benchmarks
For LIAR-RAW, we extended the public dataset LIAR-PLUS (Alhindi et al., 2018) with relevant raw reports, containing fine-grained claims from Politifact.
9 papers · 0 benchmarks
For RAWFC, we constructed it from scratch by collecting the claims from Snopes and relevant raw reports by retrieving claim keywords.
6 papers · 1 benchmark
Contains 3,689,229 English news articles on politics, gathered from 11 United States (US) media outlets covering a broad ideological spectrum.
3 papers · 0 benchmarks
COVID-CQ is a stance data set of user-generated content on Twitter in the context of COVID-19.
3 papers · 0 benchmarks
CoVaxLies v1 includes 17 known Misinformation Targets (MisTs) found on Twitter about the covid-19 vaccines.
3 papers · 0 benchmarks
Conversational Stance Detection (CSD) is a dataset with annotations of stances and the structures of conversation threads.
3 papers · 0 benchmarks
CIC (Catalonia Independence Corpus)
The dataset is annotated with stance towards one topic, namely, the independence of Catalonia.
2 papers · 3 benchmarks
CoVaxFrames includes 113 Vaccine Hesitancy Framings found on Twitter about the COVID-19 vaccines.
2 papers · 0 benchmarks
CoVaxLies v2 includes 47 Misinformation Targets (MisTs) found on Twitter about the COVID-19 vaccines.
2 papers · 0 benchmarks
MMVax-Stance includes 113 Vaccine Hesitancy Framings found on Twitter about the COVID-19 vaccines.
2 papers · 0 benchmarks
Includes Russian tweets and news comments from multiple sources, covering multiple stories, as well as text classification approaches to stance detection as benchmarks over this data in this language.
2 papers · 1 benchmark
The "Stance Detection in COVID-19 Tweets" dataset represents an evolution of stance detection research, tailored to address the unique and urgent challenges presented by the COVID-19 pandemic.
2 papers · 0 benchmarks
The data set contains 2500 manually-stance-labeled tweets, 1250 for each candidate (Joe Biden and Donald Trump).
2 papers · 2 benchmarks
WT-WT (Will-They-Won't-They)
Will-They-Won't-They (WT-WT) is a large dataset of English tweets targeted at stance detection for the rumor verification task.
2 papers · 0 benchmarks
COVMis-Stance is a stance detection dataset for COVID-19 misinformation.
1 paper · 0 benchmarks
Dhoroni (Dhoroni: A Multi-Perspective Bengali Climate Change and Environmental News Dataset)
Climate change poses critical challenges globally, disproportionately affecting low-income countries that often lack resources and linguistic representation on the international stage.
1 paper · 1 benchmark
The ExaASC dataset is a dataset for Target-based Stance Detection in the Arabic Language that contains different types of targets like persons, entities and events.
1 paper · 0 benchmarks
HpVaxFrames includes 64 Vaccine Hesitancy Framings found on Twitter about the HPV vaccines.
1 paper · 0 benchmarks
This dataset of medical misinformation was collected and is published by Kempelen Institute of Intelligent Technologies (KInIT).
1 paper · 0 benchmarks
A novel stance detection dataset covering 419 different controversial issues and their related pros and cons collected by procon.org in nonpartisan format.
1 paper · 0 benchmarks
StEduCov, a dataset annotated for stances toward online education during the COVID-19 pandemic.
1 paper · 1 benchmark
SemEval-2016 Task 6, titled "Stance Detection in Tweets," provides a specialized dataset for the computational linguistics and natural language processing (NLP) communities to explore and analyze users' positions towards certain targets,…
1 paper · 0 benchmarks
Combines CoVaxFrames and HpVaxFrames into a unified dataset of 113 Vaccine Hesitancy Framings found on Twitter about the COVID-19 vaccines and 64 Vaccine Hesitancy Framings found on Twitter about the HPV vaccines.
1 paper · 0 benchmarks
A Natural Language Resource for Learning to Recognize Misinformation about the COVID-19 and HPV Vaccines.
1 paper · 0 benchmarks
1 paper · 0 benchmarks
zulu-stance (Zulu Stance)
This is a stance detection dataset in the Zulu language.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.