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  "doi": null,
  "retrievedAt": "2026-07-16T18:19:08.025Z",
  "createdAt": "2026-05-09T07:09:36.975Z",
  "updatedAt": "2026-05-09T07:09:36.975Z",
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    "text": "User self-selection rather than algorithmic recommendations drives the consumption of politically segregated content on YouTube, though this finding about content navigation does not directly bound the algorithmic contribution to affective polarization through the out-group hostility channel."
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      "text": "Hosseinmardi et al. (2021) analyzed browser traces of 300,000 US YouTube users from 2016-2019 and found that consumption of far-right content was concentrated among users who already held those views and arrived via off-platform referrals.",
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      "text": "YouTube recommendations rarely moved ordinary users toward extreme content, contradicting the algorithmic rabbit-hole hypothesis.",
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      "text": "Barberá (2015) documented strong ideological clustering in Twitter following networks, establishing that the network-segregation baseline is primarily user-driven.",
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