United States

To what extent does the YouTube recommendation algorithm push users into echo chambers, rabbit holes, or radicalization pathways? Using a novel method to estimate the ideology of YouTube videos and an original audit design, we find that YouTube users experience mild ideological echo chambers, but these appear to be driven primarily by user behavior.  We also demonstrate that the recommendation algorithm prioritizes content that is similar to what the user is currently watching, producing “content rabbit holes”. However, we do not find evidence of radicalization pathways where users are driven into increasingly extreme content rabbit holes. Instead, we find that YouTube’s recommendations move users, regardless of ideology, toward moderately conservative content and an increasingly narrow range of ideological content the longer they follow YouTube’s recommendations.

Deceptive online networks are coordinated efforts that use identity deception to pursue strategic political or financial goals. During the US 2020 elections, these networks reached at least 37 million Facebook and 3 million Instagram users, representing 15% and 2% of the platforms’ active US adult users, respectively. Only 3 networks out of 49—1 network with explicitly political aims and 2 that appeared to use politics as a lure for profit—were responsible for over 70% of users reached. Notably, accounts unaffiliated with the networks played an important role in facilitating this reach by resharing content the three networks produced. Deceptive networks, regardless of whether their goals were political or financial, reached users who were older, more conservative, more frequently exposed to content from untrustworthy sources, and spent more time on Facebook.