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          "tiktok",
          "youtube",
          "x"
        ],
        "delta_wow": 0.12,
        "summary": "In this sample batch, curiosity-gap and how-to openings appear frequently among higher relative ER posts. Treat as directional — sample data.",
        "sources": [
          "rss",
          "youtube",
          "reddit",
          "x"
        ],
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        "sources": [
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        ],
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        "title": "How do I benchmark my AI search performance against my industry?",
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          "facebook"
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          "rss"
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        "id": "trend-2026-11-micro-creators",
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      "disclaimer": "Correlational estimate from public/authorized posts blended with approximate public benchmarks; not a platform guarantee."
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      "disclaimer": "Correlational estimate from public/authorized posts blended with approximate public benchmarks; not a platform guarantee."
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      "disclaimer": "Correlational estimate from public/authorized posts blended with approximate public benchmarks; not a platform guarantee."
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      "disclaimer": "Correlational estimate from public/authorized posts blended with approximate public benchmarks; not a platform guarantee."
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      "disclaimer": "Correlational estimate from public/authorized posts blended with approximate public benchmarks; not a platform guarantee."
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      "disclaimer": "Correlational estimate from public/authorized posts blended with approximate public benchmarks; not a platform guarantee."
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          "hour": 3,
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        {
          "dow": 6,
          "hour": 4,
          "score": 0,
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        },
        {
          "dow": 6,
          "hour": 5,
          "score": 0.1018,
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        },
        {
          "dow": 6,
          "hour": 6,
          "score": 0.2037,
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        {
          "dow": 6,
          "hour": 7,
          "score": 0.3055,
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        {
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          "score": 0.3055,
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        {
          "dow": 6,
          "hour": 9,
          "score": 0.4709,
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        },
        {
          "dow": 6,
          "hour": 10,
          "score": 0.6363,
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        },
        {
          "dow": 6,
          "hour": 11,
          "score": 0.6363,
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        {
          "dow": 6,
          "hour": 12,
          "score": 0.4709,
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        },
        {
          "dow": 6,
          "hour": 13,
          "score": 0.3055,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 14,
          "score": 0.4709,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 15,
          "score": 0.6363,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 16,
          "score": 0.6363,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 17,
          "score": 0.4709,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 18,
          "score": 0.3055,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 19,
          "score": 0.3055,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 20,
          "score": 0.3055,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 21,
          "score": 0.3055,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 22,
          "score": 0.25,
          "n": 0
        },
        {
          "dow": 6,
          "hour": 23,
          "score": 0.1481,
          "n": 0
        }
      ],
      "top_windows": [
        {
          "label": "Mon 19:00–21:00",
          "score": 0.8842
        },
        {
          "label": "Tue 19:00–21:00",
          "score": 0.8842
        },
        {
          "label": "Wed 19:00–21:00",
          "score": 0.8842
        }
      ],
      "disclaimer": "Correlational estimate from public/authorized posts blended with approximate public benchmarks; not a platform guarantee."
    }
  },
  "meta": {
    "generated_at": "2026-11-05T21:23:03.300Z",
    "heuristic_version": "1.0.0",
    "license_notes": "Public landing snapshots use API/RSS metadata, fixtures, and approximate benchmarks. Not full-text republishing.",
    "sample": true
  }
}