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random_walker's profile
Arvind Narayanan
Arvind Narayanan
Arvind Narayanan
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@random_walker

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Arvind NarayananVerified account

@random_walker

Princeton prof. I use Twitter to share my research and commentary on algorithmic fairness, AI hype, the surveillance economy, tech policy, and academic life.

Princeton, NJ
cs.princeton.edu/~arvindn/
Joined December 2007

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    Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

    A new paper has been making the rounds with the intriguing claim that YouTube has a *de-radicalizing* influence. https://arxiv.org/abs/1912.11211  Having read the paper, I wanted to call it wrong, but that would give the paper too much credit, because it is not even wrong. Let me explain.

    4:26 AM - 29 Dec 2019
    • 2,027 Retweets
    • 4,791 Likes
    • Alan Chan Naomi campbell Vincent Carlino Nathalie Pignard-Cheynel GoodTimesAheadBot Daniel Burton the dave 🚀 𝕯𝖗𝖆𝖌𝖔𝖓 𝕲𝖔𝖉 🚀 Catherine
    82 replies 2,027 retweets 4,791 likes
      1. New conversation
      2. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        Radicalization via YouTube, as widely understood, is when someone watches a few partisan videos and unwittingly starts a feedback loop in which the algorithm gradually recommends more and more extreme content and the viewer starts to believe more and more of it.

        12 replies 109 retweets 852 likes
        Show this thread
      3. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        The key is that the user’s beliefs, preferences, and behavior shift over time, and the algorithm both learns and encourages this, nudging the user gradually. But this study didn’t analyze real users. So the crucial question becomes: what model of user behavior did they use?

        1 reply 83 retweets 772 likes
        Show this thread
      4. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        The answer: they didn’t! They reached their sweeping conclusions by analyzing YouTube *without logging in*, based on sidebar recommendations for a sample of channels (not even the user’s home page because, again, there’s no user). Whatever they measured, it’s not radicalization.

        15 replies 140 retweets 1,286 likes
        Show this thread
      5. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        Arvind Narayanan Retweeted Mark Ledwich  🎨 🌐

        Sidenote: the first author has been on a diatribe about the media, even in the thread introducing the paper. It doesn’t undermine the paper by itself, but given that they disingenuously exclude how radicalization might actually work, it… raises questions.https://twitter.com/mark_ledwich/status/1210743217982803970 …

        Arvind Narayanan added,

        Mark Ledwich  🎨 🌐 @mark_ledwich
        4. My new article explains in detail. It takes aim at the NYT (in particular, @kevinroose) who have been on myth-filled crusade vs social media. We should start questioning the authoritative status of outlets that have soiled themselves with agendas. https://medium.com/@markoledwich/youtube-radicalization-an-authoritative-saucy-story-28f73953ed17 …
        Show this thread
        7 replies 75 retweets 850 likes
        Show this thread
      6. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        Others have pointed out many more limitations of the paper, including the fact that it claims to refute years of allegations of radicalization using late-2019 measurements. Sure, but that’s a bit like pointing out typos in the article that announced "Dewey Defeats Truman".

        1 reply 49 retweets 746 likes
        Show this thread
      7. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        Incidentally, I spent about a year studying YouTube radicalization with several students. We dismissed simplistic research designs (like the one in the paper) by about week 2, and realized that the phenomenon results from users/the algorithm/video creators adapting to each other.

        8 replies 138 retweets 1,158 likes
        Show this thread
      8. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        Let’s not forget: the peddlers of extreme content adversarially navigate YouTube’s algorithm, optimizing the clickbaitiness of their video thumbnails and titles, while reputable sources attempt to maintain some semblance of impartiality. (None of this is modeled in the paper.)

        7 replies 105 retweets 879 likes
        Show this thread
      9. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        After tussling with these complexities, my students and I ended up with nothing publishable because we realized that there’s no good way for external researchers to quantitatively study radicalization. I think YouTube can study it internally, but only in a very limited way.

        16 replies 112 retweets 958 likes
        Show this thread
      10. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        If you’re wondering how such a widely discussed problem has attracted so little scientific study before this paper, that’s exactly why. Many have tried, but chose to say nothing rather than publish meaningless results, leaving the field open for authors with lower standards.

        13 replies 148 retweets 1,207 likes
        Show this thread
      11. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        In our data-driven world, the claim that we don’t have a good way to study something quantitatively may sound shocking. The reality even worse — in many cases we don’t even have the vocabulary to ask meaningful quantitative *questions* about complex socio-technical systems.

        16 replies 444 retweets 1,815 likes
        Show this thread
      12. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        Consider the paper’s definition of radicalization: "YouTube’s algorithm [exposes users] to more extreme content than they would otherwise." Savvy readers are probably screaming: There is no "otherwise"! There is no YouTube without the algorithm! There is no neutral!

        7 replies 94 retweets 997 likes
        Show this thread
      13. Arvind Narayanan‏Verified account @random_walker 29 Dec 2019

        That’s the note on which I’d like to end: a plea to consider that the available quantitative methods can’t answer everything. And I want to thank the journalists who’ve been doing the next best thing — telling the stories of people led down a rabbit hole by YouTube’s algorithm.

        38 replies 162 retweets 1,399 likes
        Show this thread
      14. End of conversation

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