{
  "identifier": "wCV7c6Mn",
  "argumentId": "cmoxjsof5030t8cssoi1hm35e",
  "permalink": "https://www.isonomia.app/a/wCV7c6Mn",
  "version": 1,
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  "isoId": "iso:argument:wCV7c6Mn",
  "isoUrl": "https://www.isonomia.app/iso/argument/wCV7c6Mn",
  "doi": null,
  "retrievedAt": "2026-07-16T18:19:32.791Z",
  "createdAt": "2026-05-08T23:30:20.706Z",
  "updatedAt": "2026-05-08T23:30:20.706Z",
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    "text": "Pre-algorithmic confounders including homophily, partisan identity strength, and cable TV are documented to be quantitatively larger contributors to polarization than algorithmic ranking in available studies, though their precise share of post-2012 growth is not established."
  },
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      "text": "Iyengar et al. (2012) shows affective polarization was substantial in the 1980s, establishing that partisan identity strength predates social media.",
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    },
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      "text": "Bakshy et al. (2015) found that user choice (homophily) is the larger contributor to ideological exposure filtering than algorithmic ranking on Facebook.",
      "isImplicit": false
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      "text": "Eady et al. (2019) found most Twitter users are exposed to substantial cross-cutting content, and Eady et al. (2023) found foreign-influence exposure concentrated in already-polarized minorities with no attitude change.",
      "isImplicit": false
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        "cqKey": "alternative_hypothesis?",
        "text": "Is there a plausible alternative hypothesis that has not been considered or that would explain the facts at least as well?",
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