mlsanityData to 7 Oct 2026

A simple but tough-to-beat baseline for the Fake News Challenge stance detection task

arXiv 1707.03264 ↗First posted 11 Jul 2017cs.CLcited by 26

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Abstract (arXiv)

Identifying public misinformation is a complicated and challenging task. An important part of checking the veracity of a specific claim is to evaluate the stance different news sources take towards the assertion. Automatic stance evaluation, i.e. stance detection, would arguably facilitate the process of fact checking. In this paper, we present our stance detection system which claimed third place in Stage 1 of the Fake News Challenge. Despite our straightforward approach, our system performs at a competitive level with the complex ensembles of the top two winning teams. We therefore propose our system as the 'simple but tough-to-beat baseline' for the Fake News Challenge stance detection task.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jul 2017.

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Citing papers per year: 2021: 10; 2022: 10; 2023: 0; 2024: 3; 2025: 2; 2026: 1.

26 papers.

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  1. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  2. 2022Logical Fallacy Detectioncited by 25
  3. 2022Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claimscited by 10
  4. 2021Is Stance Detection Topic-Independent and Cross-topic Generalizable? -- A Reproduction Studycited by 9
  5. 2022Stanceosaurus: Classifying Stance Towards Multilingual Misinformationcited by 8
  6. 2022Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networkscited by 6
  7. 2021A transformer based approach for fighting COVID-19 fake newscited by 5
  8. 2022Data Augmentation for Biomedical Factoid Question Answeringcited by 5
  9. 2021TIB's Visual Analytics Group at MediaEval '20: Detecting Fake News on Corona Virus and 5G Conspiracycited by 4
  10. 2022ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translationcited by 4
  11. 2021WhatTheWikiFact: Fact-Checking Claims Against Wikipediacited by 3
  12. 2021Hostility Detection and Covid-19 Fake News Detection in Social Mediacited by 2
14 more
  1. 2021Back to the Basics: A Quantitative Analysis of Statistical and Graph-Based Term Weighting Schemes for Keyword Extractioncited by 2
  2. 2021Tribrid: Stance Classification with Neural Inconsistency Detectioncited by 2
  3. 2025Efficiency and Effectiveness of LLM-Based Summarization of Evidence in Crowdsourced Fact-Checkingcited by 2
  4. 2022Incongruity Detection between Bangla News Headline and Body Content through Graph Neural Networkcited by 1
  5. 2024SocialPET: Socially Informed Pattern Exploiting Training for Few-Shot Stance Detection in Social Mediacited by 1
  6. 2026Reliable News or Propagandist News? A Neurosymbolic Model Using Genre, Topic, and Persuasion Techniques to Improve Robustness in Classificationcited by 1
  7. 2021SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?cited by 0
  8. 2021Leveraging Commonsense Knowledge on Classifying False News and Determining Checkworthiness of Claimscited by 0
  9. 2022UofA-Truth at Factify 2022 : Transformer And Transfer Learning Based Multi-Modal Fact-Checkingcited by 0
  10. 2022BaIT: Barometer for Information Trustworthinesscited by 0
  11. 2022Combination Of Convolution Neural Networks And Deep Neural Networks For Fake News Detectioncited by 0
  12. 2024TeClass: A Human-Annotated Relevance-based Headline Classification and Generation Dataset for Telugucited by 0
  13. 2024Sequential Classification of Misinformationcited by 0
  14. 2025BERT-based model for Vietnamese Fact Verification Datasetcited by 0