A Longitudinal Analysis of YouTube's Promotion of Conspiracy Videos

TL;DR

This study analyzes YouTube's efforts to reduce the promotion of conspiracy videos by developing a classifier and emulating the recommendation algorithm over a year, revealing trends and filter-bubble effects.

Contribution

It introduces a novel classifier for identifying conspiracy videos and provides a longitudinal analysis of YouTube's recommendation changes and their impact.

Findings

Reduction in promoted conspiracy videos over time

Presence of filter-bubble effects in recommendations

Insights into YouTube's algorithmic moderation efforts

Abstract

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.