# A Longitudinal Analysis of YouTube's Promotion of Conspiracy Videos

arXiv: https://arxiv.org/abs/2003.03318 · HTML: https://mlsanity.com/paper/2003.03318/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2020.

## Built on by (most cited first, 9 of 9)

- [Problematic Machine Behavior: A Systematic Literature Review of Algorithm Audits](https://mlsanity.com/paper/2102.04256/) (2021)
- [Reason Against the Machine: Future Directions for Mass Online Deliberation](https://mlsanity.com/paper/2107.12711/) (2021)
- [Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability](https://mlsanity.com/paper/2107.00833/) (2021)
- [In the Eye of the Beholder: Robust Prediction with Causal User Modeling](https://mlsanity.com/paper/2206.00416/) (2022)
- [System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes](https://mlsanity.com/paper/2406.01611/) (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)
- [Uncovering Conspiratorial Narratives within Arabic Online Content](https://mlsanity.com/paper/2504.14037/) (2025)

## Abstract (arXiv)

Conspiracy theories have flourished on social media, raising concerns that such content is fueling the spread of disinformation, supporting extremist ideologies, and in some cases, leading to violence. Under increased scrutiny and pressure from legislators and the public, YouTube announced efforts to change their recommendation algorithms so that the most egregious conspiracy videos are demoted and demonetized. To verify this claim, we have developed a classifier for automatically determining if a video is conspiratorial (e.g., the moon landing was faked, the pyramids of Giza were built by aliens, end of the world prophecies, etc.). We coupled this classifier with an emulation of YouTube's watch-next algorithm on more than a thousand popular informational channels to obtain a year-long picture of the videos actively promoted by YouTube. We also obtained trends of the so-called filter-bubble effect for conspiracy theories.