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    "story_id": "mp-2026-07-21-027",
    "source_story_id": "tmp-story-exceptionality-bias-social-feeds",
    "edition_id": "mp-2026-07-21-morning-0012",
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    "position": 16,
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    "section": "policy",
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    "headline": "The Feed Overcounts the Exceptional",
    "slug": "the-feed-overcounts-the-exceptional",
    "dek": "People select unusually exciting experiences to share, leading viewers to overestimate how common those events are.",
    "summary": "People select unusually exciting experiences to share, leading viewers to overestimate how common those events are.",
    "body_text": "Virginia Tech researchers report that social-media users preferentially share rare and exciting experiences, while audiences exposed to those feeds infer that the exceptional events happen more often than they really do. That human selection bias can shape the feed before any ranking algorithm amplifies it, and viewers may then seek more unusual experiences to post themselves. The study isolates a behavioral mechanism; it does not say platforms, recommendation systems, or individual users all contribute equally.",
    "why_it_matters": "People select unusually exciting experiences to share, leading viewers to overestimate how common those events are.",
    "limitations": [
      "The study isolates a behavioral mechanism; it does not say platforms, recommendation systems, or individual users all contribute equally."
    ],
    "importance": 7,
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    "first_published_at": "2026-07-21T09:00:00.000-04:00",
    "modified_at": "2026-07-21T09:00:00.000-04:00",
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        "text": "People select unusually exciting experiences to share, leading viewers to overestimate how common those events are.",
        "source_ids": [
          "source-2026-07-21-016"
        ],
        "qualification": "The study isolates a behavioral mechanism; it does not say platforms, recommendation systems, or individual users all contribute equally."
      }
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    "source_ids": [
      "source-2026-07-21-016"
    ],
    "tags": [
      "social media",
      "behavior",
      "selection bias"
    ],
    "image_url": null,
    "corrections": []
  },
  "sources": [
    {
      "source_id": "source-2026-07-21-016",
      "title": "Virginia Tech via Newswise: Human bias in social feeds",
      "publisher": "Virginia Tech via Newswise",
      "url": "https://www.newswise.com/articles/research-reveals-how-human-bias-shapes-social-media-feeds",
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      "source_type": "secondary_reporting",
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      "published_at": null,
      "accessed_at": "2026-07-21T08:27:27.115-04:00",
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  "corrections": [],
  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "The Feed Overcounts the Exceptional",
    "publisher": "The Machine Press",
    "published_at": "2026-07-21T09:00:00.000-04:00",
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