Trending

The trending endpoint returns the top terms driving conversation on a topic or watchlist right now, ranked by a rolling z-score against a 14-day baseline. It is the fastest way to answer “what is everyone actually talking about” in one call, and it is available on every tier — including the free Watch trial. Trending answers a different question from Alerts and Narrative:

Surface	Question	Shape
Trending	”Which words are spiking?”	Ranked list of terms with z-scores
Narrative	”What is the story those words form?”	Editorial summary + sub-narrative weights
Alerts	”What just happened that needs attention?”	Discrete events with severity, spread, IOCs

Use trending as the state view — a tile on a dashboard, a feed in a wallboard, a row in an exec digest. Use alerts when you need a push-shaped, machine-routable event.

The endpoints

Endpoint	Tier	Returns
`GET /v1/topics/{topic}/trending`	Watch+	Top terms on a curated topic
`GET /v1/watchlists/{id}/trending`	See+	Top terms inside your watchlist’s term scope

Both return the same JSON shape. Code written for one works on the other — the only difference is the scope identifier in the response (topic vs. watchlist_id).

The response envelope

{
  "topic": "global",
  "snapshot_id": "2026-05-19T13:00:00Z",
  "terms": [
    { "term": "Iran",       "score": 847.2, "rank": 1, "delta_24h": 6.6,  "post_count": 12480 },
    { "term": "Eurovision", "score": 412.0, "rank": 2, "delta_24h": 1.8,  "post_count":  6210 },
    { "term": "ECB",        "score": 289.4, "rank": 3, "delta_24h": 0.9,  "post_count":  4055 },
    { "term": "Bitcoin",    "score": 211.7, "rank": 4, "delta_24h": -0.3, "post_count":  3142 }
  ],
  "count": 50,
  "data_freshness": { "snapshot_age_seconds": 312, "level": "ok" },
  "query_window": { "hours": 24, "effective_hours": 24 }
}

Field guide

Field	Type	Meaning
`topic` / `watchlist_id`	string	Scope identifier — exactly one is present
`snapshot_id`	ISO-8601 UTC	Pipeline run that produced this response. Pin to it for reproducibility.
`terms[]`	array	Ranked term list, length capped per tier (see below)
`terms[].term`	string	Surface form, lowercased, deduped against synonyms
`terms[].score`	float	Rolling z-score against 14-day baseline. Higher = more anomalous
`terms[].rank`	int	1-indexed position in this snapshot
`terms[].delta_24h`	float	Score change vs. same window 24h ago. Positive = accelerating
`terms[].post_count`	int	Raw posts mentioning the term in the window
`count`	int	Total terms returned (≤ tier cap)
`data_freshness.snapshot_age_seconds`	int	Seconds since pipeline produced this snapshot
`data_freshness.level`	enum	`ok`, `degraded`, `stale` — UI traffic light
`query_window.hours`	int	What you asked for
`query_window.effective_hours`	int	What you got after tier clamping

score is not comparable across topics — global and cyber have different baselines. delta_24h is comparable across snapshots within the same topic.

Query parameters

Param	Default	Watch cap	See cap	Know cap	Notes
`hours`	24	24	72	168	Rolling window length. Above-cap requests are silently clamped — see `query_window.effective_hours`
`limit`	50	20	100	500	Hard ceiling on returned terms
`min_score`	—	—	—	—	Filter out terms below this z-score
`exclude_terms`	—	—	—	—	Comma-separated list to suppress (e.g. brand stopwords)

A request for limit=10000&hours=720 on a Watch key returns at most 20 terms over 24h, with query_window.effective_hours: 24 so your UI knows what it actually got.

Calling it

curl "https://intel-v1.exorde.io/v1/topics/global/trending?limit=10" \
  -H "X-API-Key: $EXORDE_API_KEY"

import os, httpx

r = httpx.get(
    "https://intel-v1.exorde.io/v1/topics/global/trending",
    params={"limit": 10},
    headers={"X-API-Key": os.environ["EXORDE_API_KEY"]},
    timeout=10,
).json()

print(f"snapshot {r['snapshot_id']}  age={r['data_freshness']['snapshot_age_seconds']}s")
for t in r["terms"]:
    print(f"{t['rank']:>2}. {t['term']:<25} z={t['score']:>7.1f}  Δ24h={t['delta_24h']:+.1f}")

const r = await fetch(
  "https://intel-v1.exorde.io/v1/topics/global/trending?limit=10",
  { headers: { "X-API-Key": process.env.EXORDE_API_KEY } }
).then(r => r.json());

r.terms.forEach(t =>
  console.log(`${t.rank}. ${t.term}  z=${t.score.toFixed(1)}  Δ24h=${t.delta_24h}`)
);

$r = Invoke-RestMethod `
  -Uri "https://intel-v1.exorde.io/v1/topics/global/trending?limit=10" `
  -Headers @{ "X-API-Key" = $env:EXORDE_API_KEY }

$r.terms | Select-Object rank, term, score, delta_24h | Format-Table

Reading the score

score is a rolling z-score — how many standard deviations above the 14-day baseline this term’s volume sits. Rough guidance:

Score range	Interpretation
`< 50`	Background noise on a high-volume topic
`50 – 200`	Normal trending — recurring storyline, scheduled event
`200 – 500`	Genuinely elevated — a real story is forming
`> 500`	Loud — the term is dominating the snapshot
`> 1000`	Rare. Usually maps to a major breaking story or coordinated push

Combine score with delta_24h to distinguish accelerating from decaying stories:

High score + high delta_24h → story breaking now
High score + low or negative delta_24h → story peaked, decaying
Low score + high delta_24h → emerging, worth watching

Same shape, scoped to your watchlist’s terms. Useful when the top terms inside your brand or threat scope diverge from the topic baseline.

curl https://intel-v1.exorde.io/v1/watchlists/wl_01HXYZ.../trending \
  -H "X-API-Key: $EXORDE_API_KEY"

{
  "watchlist_id": "wl_01HXYZ7DKMSV2X9WJEQ5RQ4N3F",
  "name": "acme-monitoring",
  "snapshot_id": "2026-05-19T13:00:00Z",
  "terms": [
    { "term": "acme",     "score": 142.3, "rank": 1, "delta_24h":  0.4, "post_count": 1820 },
    { "term": "ceo",      "score":  87.1, "rank": 2, "delta_24h":  1.2, "post_count":  920 },
    { "term": "earnings", "score":  61.8, "rank": 3, "delta_24h":  3.7, "post_count":  610 }
  ],
  "data_freshness": { "snapshot_age_seconds": 312, "level": "ok" }
}

earnings accelerating fast (delta_24h: 3.7) on a brand watchlist is the kind of signal a comms team wants to see before the quarterly press cycle. See Topics and watchlists for watchlist setup.

Cadence and freshness

Snapshots refresh every few minutes. Polling faster than the snapshot cadence returns the same payload — burns RPM for nothing.

Use case	Tier	Cadence	Daily call cost
Dashboard tile	Watch	every 5 min	~290 / day
Live wallboard	See	every 60s	~1,440 / day
Real-time exec view	Know	every 15s	~5,760 / day

Below 15-second freshness on trending you’re chasing snapshot publication latency, not the data — there’s nothing newer to fetch. For sub-second event delivery, use Alerts via webhook. Always read X-RateLimit-Remaining and back off when it drops below 20% of X-RateLimit-Limit. Full pattern: Rate limits.

Common patterns

Filter out predictable churn

Some terms appear permanently elevated on certain topics (bitcoin on finance, russia on disinfo). Mute them client-side or with exclude_terms:

EXCLUDE = {"bitcoin", "ethereum", "russia"}
fresh = [t for t in r["terms"] if t["term"].lower() not in EXCLUDE]

Track new entrants

Compare consecutive snapshots and surface terms that just appeared in the top N:

prev_terms = {t["term"] for t in prev_snapshot["terms"][:25]}
new_entrants = [t for t in current["terms"][:25] if t["term"] not in prev_terms]

A term that wasn’t in the top 25 an hour ago and now sits at rank 7 is usually worth a look.

Cross-topic comparison

Pull trending on global, cyber, finance, disinfo in parallel for a one-page situational view. Score is not comparable across topics, but presence and rank are. See Use cases recipe 5.

Snapshots and reproducibility

Every response carries snapshot_id. Pin to a snapshot when you need to reproduce an analysis or align trending with a specific narrative or alert state. Snapshots are retained for the same window your tier allows on history depth (see Tiers — history depth caps).

# Pin a query to the snapshot the alert was emitted under
curl "https://intel-v1.exorde.io/v1/topics/global/trending?snapshot_id=2026-05-19T13:00:00Z" \
  -H "X-API-Key: $EXORDE_API_KEY"

A 410 snapshot_expired envelope means the snapshot rolled out of retention — refetch with latest. See Errors.

Operational guidance

Don’t compare score across topics. Different baselines, different volume regimes. rank and delta_24h are the cross-topic-safe fields.
Cache by snapshot_id. Same snapshot_id = same payload. Re-fetch only when you suspect a new snapshot exists (every few minutes).
Pair trending with narrative on dashboards: the term list is the spike, the narrative is the story. One without the other under-delivers.
For watchlists, expect lower scores. A watchlist filters the universe — the top term in your brand scope may have a score of 80 while global has terms above 800. The math is the same; the volume is smaller.
Trending counts against RPM like any other call. Don’t poll under the snapshot cadence.

You want	Use this
”Volume of X over the last week”	`/v1/topics/{t}/volume`
”Volume broken down by keyword”	`/v1/topics/{t}/volume/keywords`
”Find posts mentioning X”	`/v1/topics/{t}/search` (See+)
“Which entities co-occur”	`/v1/topics/{t}/entities/cooccurrence` (See+)
“Push me when something spikes”	Alerts via webhook

Trending is the ranked-state view. Everything else is volume, content, or events.

Last reviewed: 2026-05-19. API version 1.2.8.

Getting started

Core concepts

Signals

Build

The endpoints

The response envelope

Field guide

Query parameters

Calling it

Reading the score

Cadence and freshness

Common patterns

Filter out predictable churn

Track new entrants

Cross-topic comparison

Snapshots and reproducibility

Operational guidance

​The endpoints

​The response envelope

​Field guide

​Query parameters

​Calling it

​Reading the score

​Trending on a watchlist

​Cadence and freshness

​Common patterns

​Filter out predictable churn

​Track new entrants

​Cross-topic comparison

​Snapshots and reproducibility

​Operational guidance

​What’s not trending

The endpoints

The response envelope

Field guide

Query parameters

Calling it

Reading the score

Trending on a watchlist

Cadence and freshness

Common patterns

Filter out predictable churn

Track new entrants

Cross-topic comparison

Snapshots and reproducibility

Operational guidance

What’s not trending