## panorama/brand-mentions

`GET /v1/panorama/brand-mentions`

Collect a bounded native social search sample for one brand, with original evidence, engagement, dates and per-source coverage. Defaults to Reddit, Hacker News, X, TikTok, Instagram and YouTube, plus configured Bluesky; platforms selects supported alternatives. Strict dates exclude unknown or out-of-window records. Optional indexed history is a separate measurement; source eligibility and workflow limits apply.

*Brand mentions*

| Parameter | Required | Description |
| --- | --- | --- |
| `brand` | yes | The brand or product to find mentions of — e.g. `minoapi` |
| `platforms` | no | CSV of supported sources: reddit,hackernews,bluesky,github,x,tiktok,instagram,youtube,linkedin,threads,pinterest. Default the six example sources. Each remains subject to eligibility, funding, deadlines and limits. — e.g. `reddit,hackernews,x,tiktok,instagram,youtube` |
| `date_mode` | no | ranked (default) retains date-labelled matches; strict excludes unknown and out-of-window dates. — e.g. `strict` |
| `per_source_limit` | no | Integer 1–50, default25. Bounded sample per source; no full-platform count. — e.g. `25` |
| `lookback_days` | no | Integer1–366, default30. — e.g. `30` |
| `context` | no | Optional subject context, at most1000 characters. Adds a bounded hint from the caller’s positive context to native search and prioritises returned candidates; inspect query_plan and source queries. Also guides optional Jev classification where supported. No inferred aliases or identity guarantee. — e.g. `Mercury, the business banking service; not the planet.` |
| `relevance` | no | none (default) or jev. Optional funded classification on at most20 candidates per brand, balanced across sources within relevance tiers. All original evidence and sampled arithmetic remain available. Inspect selection and classified counts; capacity and funding can leave records unclassified. — e.g. `none` |
| `include_history` | no | Optional indexed web summary, trends and example citations. Defaultfalse. Reported separately from social sample metrics and subject to the same workflow supply budget. — e.g. `true` |
| `enrich` | no | none (default), comments or transcripts. Add context to at most3 supported posts, capped at10 comments or8000 transcript characters each. Enrichment is not counted as another mention. — e.g. `comments` |
| `dry_run` | no | Read a zero-credit estimate without fetching sources, running AI, or reserving credits. Cache status is a snapshot, not a guarantee at execution. — e.g. `1` |

**Cost:** 5 credits at list price per successful uncached response; variable-cost operations may quote or settle a different charge. Confirmed uncharged or refunded failures report zero. Pending reconciliation can report credits_used:null; retain request_id and the original idempotency key.

```bash
curl "https://www.monocrawl.com/v1/panorama/brand-mentions?brand=minoapi" \
  -H "x-api-key: mn_your_key_here"
```

### Response data

Illustrative abbreviated data; documented core fields are optional and may be null. Additional source fields are allowed.

```json
{
  "schema_version": "social-evidence-v2",
  "scope": "native_social_search_sample",
  "brand": "My Brand",
  "mentions": 1,
  "engagement": 12,
  "items": [
    {
      "id": "101",
      "platform": "hackernews",
      "source": "hackernews",
      "title": "Using My Brand",
      "text": null,
      "url": "https://news.ycombinator.com/item?id=101",
      "canonical_url": "https://news.ycombinator.com/item?id=101",
      "author": {
        "id": null,
        "handle": "example_reader",
        "name": null,
        "url": null
      },
      "metrics": {
        "likes": null,
        "score": 10,
        "comments": 2,
        "reshares": null,
        "views": null,
        "interactions": 12,
        "complete_interactions": false
      },
      "engagement": 12,
      "created_at": "2026-09-18T12:00:00.000Z",
      "fetched_at": "2026-09-19T12:00:00.000Z",
      "date_status": "within_window",
      "relevance": {
        "method": "literal_subject_match",
        "classification": "keyword_match",
        "entity_verified": false
      },
      "provenance": [
        {
          "platform": "hackernews",
          "endpoint": "search",
          "query": "My Brand",
          "params": {
            "query": "My Brand"
          }
        }
      ]
    }
  ],
  "coverage": {
    "hackernews": {
      "status": "answered",
      "fetched": 1,
      "examined": 1,
      "returned": 1,
      "deduplicated": 0,
      "within_window": 1,
      "undated": 0,
      "outside_window": 0,
      "sample_cap": 25,
      "has_more": false,
      "date_mode": "strict"
    }
  },
  "timeline": [
    {
      "date": "2026-09-18",
      "count": 1
    }
  ],
  "timeline_undated": 0,
  "query_plan": {
    "version": "panorama-context-query-v1",
    "subject": "My Brand",
    "query": "My Brand",
    "mode": "subject",
    "context_terms": [],
    "source_order": [
      "hackernews"
    ],
    "lanes": [
      {
        "platform": "hackernews",
        "query": "My Brand",
        "mode": "subject"
      }
    ],
    "literal_sources": [
      "hackernews"
    ],
    "context_sources": [],
    "max_requests_per_source": 1,
    "policy": "One bounded native search per source. Original subject remains the identity target; lexical matching is not proof of identity."
  },
  "matched_items": [],
  "candidate_items": [
    {
      "id": "101",
      "platform": "hackernews",
      "source": "hackernews",
      "title": "Using My Brand",
      "text": null,
      "url": "https://news.ycombinator.com/item?id=101",
      "canonical_url": "https://news.ycombinator.com/item?id=101",
      "author": {
        "id": null,
        "handle": "example_reader",
        "name": null,
        "url": null
      },
      "metrics": {
        "likes": null,
        "score": 10,
        "comments": 2,
        "reshares": null,
        "views": null,
        "interactions": 12,
        "complete_interactions": false
      },
      "engagement": 12,
      "created_at": "2026-09-18T12:00:00.000Z",
      "fetched_at": "2026-09-19T12:00:00.000Z",
      "date_status": "within_window",
      "relevance": {
        "method": "literal_subject_match",
        "classification": "keyword_match",
        "entity_verified": false
      },
      "provenance": [
        {
          "platform": "hackernews",
          "endpoint": "search",
          "query": "My Brand",
          "params": {
            "query": "My Brand"
          }
        }
      ]
    }
  ],
  "match_summary": {
    "status": "candidates_only",
    "collected_records": 1,
    "supported_matches": 0,
    "supported_useful_matches": 0,
    "lexical_candidates": 1,
    "unresolved_records": 0,
    "unrelated_records": 0,
    "scope": "returned_sample",
    "entity_verified": false,
    "policy": "No completed relevance classification in this illustration. The original records remain available; these are lexical candidates, not verified matches."
  }
}
```

[Field reference](https://www.monocrawl.com/docs/endpoints/panorama/brand-mentions#response) · [JSON Schema for response.data](https://www.monocrawl.com/schemas/panorama/brand-mentions.json)