Study: YouTube’s Fringe Video Viewers Aren’t Passive Zombies

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On YouTube, “viewership of far-right videos peaked in 2017,” according to Penn State political scientists Kevin Munger and Joseph Phillips, who have been studying YouTube politics and the spread of “extremist” content on the popular video platform.

In a new working paper detailing their findings, Munger and Phillips challenge the trendy notion that YouTube’s algorithms and auto-play features are responsible for radicalization, and they pan the theory that viewers of alt-right and alt-right-adjacent videos become easily “infected” like zombies.

In the paper (“A Supply and Demand Framework for YouTube Politics”), Munger and Phillips note similar panic spawned by previous communications media, including cable television. In the current narrative, they write, “YouTube audiences are at risk of far-right radicalization and this is because the YouTube algorithm that was designed to maximize the company’s profits via increased audience time on the platform has learned to show people far-right videos.”

“There exist many alternative media clusters on YouTube that explicitly define themselves in opposition to mainstream structures of knowledge production, they are remarkably popular, and they tend to skew to the right,” the authors point out. To explain this, many people have coalesced on the idea that it’s something nefarious about YouTube’s recommendation system. The author disagree:

The algorithm tends to recommend alternative media (the theory goes), leading users down a “rabbit hole” into which they become trapped, watching countless hours of alternative media content and becoming hardened opponents of liberal democratic values and mainstream knowledge production institutions. Even if we accept the premise that YouTube is an important space for radical politics, we argue that a model of YouTube media effects that centers the recommendation engine is implausible, an unfortunate update of the “hypodermic needle” model of media effects that enjoyed some prominence in the 1930s and 1940s but which has been consistently discredited ever since.

New cultural contexts demand new metaphors, so in place of the hypodermic needle, we call this the “Zombie Bite” model of YouTube radicalization. The reference is to [an August 2019] working paper (the most comprehensive quantitative analysis of YouTube politics to date) which deems people who comment on videos produced by figures associated with the “Alt-Right” as “infected,” and that this “infection” spreads.

We think this theory is incomplete, and potentially misleading. And we think that it has rapidly gained a place in the center of the study of media and politics on YouTube because it implies an obvious policy solution—one which is flattering to the journalists and academics studying the phenomenon. If only Google (which owns YouTube) would accept lower profits by changing the algorithm governing the recommendation engine, the alternative media would diminish in power and we would regain our place as the gatekeepers of knowledge. This is wishful thinking that undersells the importance of YouTube politics as a whole.

Munger and Phillips implore journalists and scholars studying social-media effects “to be much more explicit in deploying research designs that are capable of falsifying the strong Zombie Bite theory” of YouTube radicalization.

“Normatively, we desperately hope the strong version of the theory is false,” they add. “If far-right content on YouTube is uniquely powerful, zombifying people after a single exposure, liberal democracy is in a very dark place indeed.” Fortunately, the evidence suggests otherwise.

The August paper referenced (“Auditing Radicalization Pathways on YouTube”) ultimately failed “to demonstrate that the algorithm has a noteworthy effect on the audience for Alt-Right content,” write Munger and Phillips:

A random walk algorithm beginning at an Alt-Lite video and taking 5 steps randomly selecting one of the ten recommended videos will only be recommended a video from the Alt-Right approximately one out every 1,700 trips. For a random walker beginning at a “control” video from the mainstream media, the probability is so small that it is difficult to see on the graph, but it is certainly no more common than one out of every 10,000 trips.

In their own analysis, they found:

• The most extreme branches of the [Alternative Influence Network] (the Alt-Right and Alt-Lite) have been in decline since mid-2017.
• However, the Alt-Right’s remaining audience is more engaged than any other audience, in terms of likes and comments per view on their videos.
• The bulk of the growth in terms of both video production and viewership over the past two years has come from the entry of mainstream conservatives into the YouTube marketplace.

What does that mean? For one, while viewers of less extreme videos may have indeed been recommended and consumed more extreme far-right content, that doesn’t necessarily mean they were enchanted by it. Now, with the entry of (relatively) more compelling mainstream conservative content on YouTube, it seems more people are watching that. And while some folks did get deeply into hateful and far-fringe content, YouTube did not create that audience, say the study authors.

Rather, “YouTube has affordances that make content creation easy for fringe political actors who tap into an existing base of disaffected individuals alienated from the mainstream, encouraging parasocial relationships.”

Munger and Phillips’ paper has received some pushback. Rebecca Lewis, author of a 2018 paper on the “Alternative Influence Network” paper on which they rely, said that the decline in alt-right and alt-light video viewership they measured could be explained by shifts in popular far-right content creators.

“Some of the creators she included in the list of Alternative Influence Network channels have lost popularity since her study was published, while others have emerged to take their place,” notes Wired. However, this latter group was not included in the Penn State researchers’ report. Munger said the findings are preliminary and part of a working paper.”


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