mlsanityData to 14 Oct 2026

A Revisit of Fake News Dataset with Augmented Fact-checking by ChatGPT

arXiv 2312.11870 ↗First posted 19 Dec 2023cs.CLcited by 4

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Abstract (arXiv)

The proliferation of fake news has emerged as a critical issue in recent years, requiring significant efforts to detect it. However, the existing fake news detection datasets are sourced from human journalists, which are likely to have inherent bias limitations due to the highly subjective nature of this task. In this paper, we revisit the existing fake news dataset verified by human journalists with augmented fact-checking by large language models (ChatGPT), and we name the augmented fake news dataset ChatGPT-FC. We quantitatively analyze the distinctions and resemblances between human journalists and LLM in assessing news subject credibility, news creator credibility, time-sensitive, and political framing. Our findings highlight LLM's potential to serve as a preliminary screening method, offering a promising avenue to mitigate the inherent biases of human journalists and enhance fake news detection.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 17 of its 41 references that are in the map. First posted on arXiv 19 Dec 2023.

Builds on

17 of 41 references.

References · 17

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5 more
  1. 2022Dbias: Detecting biases and ensuring Fairness in news articlescited by 28
  2. 2017Some Like it Hoax: Automated Fake News Detection in Social Networkscited by 20
  3. 2022Exploring Faithful Rationale for Multi-hop Fact Verification via Salience-Aware Graph Learningcited by 15
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  5. 2020CHECKED: Chinese COVID-19 Fake News Datasetcited by 11

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 0; 2026: 1.

4 papers.

  1. 2024DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detectioncited by 41
  2. 2024What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detectioncited by 25
  3. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  4. 2026AEScorer: An Agentic Evidence-Grounded Framework for Graded Factuality Verificationcited by 0