# YouNICon: YouTube's CommuNIty of Conspiracy Videos

arXiv: https://arxiv.org/abs/2304.05274 · HTML: https://mlsanity.com/paper/2304.05274/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2023.

## Built on by (most cited first, 13 of 13)

- [ChatGPT Rates Natural Language Explanation Quality Like Humans: But on Which Scales?](https://mlsanity.com/paper/2403.17368/) (2024)
- [Harmful YouTube Video Detection: A Taxonomy of Online Harm and MLLMs as Alternative Annotators](https://mlsanity.com/paper/2411.05854/) (2024)
- [DIVERSE: A Dataset of YouTube Video Comment Stances with a Data Programming Model](https://mlsanity.com/paper/2403.03334/) (2024)
- [Assessing the Impact of Conspiracy Theories Using Large Language Models](https://mlsanity.com/paper/2412.07019/) (2024)
- [Datasets for Navigating Sensitive Topics in Recommendation Systems](https://mlsanity.com/paper/2509.07269/) (2025)
- [Algorithmic Behaviors Across Regions: A Geolocation Audit of YouTube Search for COVID-19 Misinformation Between the United States and South Africa](https://mlsanity.com/paper/2409.10168/) (2024)
- [Evaluating AI capabilities in detecting conspiracy theories on YouTube](https://mlsanity.com/paper/2505.23570/) (2025)
- [Vulnerability of LLMs' Stated Beliefs? LLMs Belief Resistance Check Through Strategic Persuasive Conversation Interventions](https://mlsanity.com/paper/2601.13590/) (2026)
- [Bye Bye Perspective API: Lessons for Building and Governing Measurement Infrastructure](https://mlsanity.com/paper/2604.25580/) (2026)
- [MetaHarm: Harmful YouTube Video Dataset Annotated by Domain Experts, GPT-4-Turbo, and Crowdworkers](https://mlsanity.com/paper/2504.16304/) (2025)
- [AILS-NTUA at SemEval-2026 Task 10: Agentic LLMs for Psycholinguistic Marker Extraction and Conspiracy Endorsement Detection](https://mlsanity.com/paper/2603.04921/) (2026)
- [Misinformation Span Detection in Videos via Audio Transcripts](https://mlsanity.com/paper/2604.21767/) (2026)
- [Agentic Detection of Online Conspiracies](https://mlsanity.com/paper/2609.30250/) (2026)

## Abstract (arXiv)

Conspiracy theories are widely propagated on social media. Among various social media services, YouTube is one of the most influential sources of news and entertainment. This paper seeks to develop a dataset, YOUNICON, to enable researchers to perform conspiracy theory detection as well as classification of videos with conspiracy theories into different topics. YOUNICON is a dataset with a large collection of videos from suspicious channels that were identified to contain conspiracy theories in a previous study (Ledwich and Zaitsev 2020). Overall, YOUNICON will enable researchers to study trends in conspiracy theories and understand how individuals can interact with the conspiracy theory producing community or channel. Our data is available at: https://doi.org/10.5281/zenodo.7466262.