📈 Market-intelligence signals
What this is & how to consume it
A GDELT-style sentiment + buzz feed over every company, ticker, crypto and commodity mentioned across the scraped boards. For each entity we compute, per time-window:
- tone (−100…+100) — VADER sentiment of the discussion, mapped to a bullish/bearish axis.
- mention volume + a z-score vs the entity's own baseline (abnormal-attention signal).
- tone momentum — is the mood improving or souring.
- tone dispersion — how contested the mood is (high = a fight).
- buzz_index (0–100) and a composite signal label, with a confidence.
⚠️ This is anonymous imageboard chatter — noisy, manipulable, and
NOT financial advice. Treat it as one weak, contrarian-leaning sentiment input,
weighted by the confidence and tone_dispersion fields.
🟢 Most bullish (positive tone)
| Entity | Cat | Tone | Buzz | n | src |
|---|
🔴 Most bearish (negative tone)
| Entity | Cat | Tone | Buzz | n | src |
|---|
🔥 Highest buzz (composite heat)
| Entity | Cat | Buzz | Signal | z | src |
|---|
📡 Volume spikes (abnormal attention)
| Entity | Cat | z-score | Tone | Signal | src |
|---|
🔎 Inspect an entity timeline
📊 Mentions over time
Mention count per time bucket (bars). Spikes = abnormal attention.
📈 Sentiment over time
Average tone per time bucket (−100 bearish … +100 bullish); the dashed line is the neutral zero baseline.
🔌 Signals API — for trading bots, notebooks & dashboards
Stable, read-only JSON. No auth, no key, CORS-enabled. Base URL:
https://qalarc.com/chanalyse. The window
parameter accepts 24h, 7d, 30d, or any
<N>h / <N>d. Optional
board= (e.g. biz) and category=
(crypto/ticker/company/commodity).
Endpoints
| Endpoint | Returns |
|---|---|
GET /api/v1/signals?window=24h | Ranked scan of every market entity (lean snapshot, no time series). Add &category=crypto to filter. |
GET /api/v1/signals/summary?window=24h | Leaderboards: most bullish / bearish / highest buzz / volume spikes. |
GET /api/v1/signals/{entity}?window=7d | One entity in full, including axis, volume_series & tone_series (the timeline charted above). |
GET /api/v1/signals.csv?window=30d | The whole scan as CSV (spreadsheet-friendly). |
Copy-paste examples
# latest crypto signals
curl "https://qalarc.com/chanalyse/api/v1/signals?window=24h&category=crypto"
# one entity's full timeline (for charting)
curl "https://qalarc.com/chanalyse/api/v1/signals/bitcoin?window=7d"
# the bullish/bearish/buzz leaderboards
curl "https://qalarc.com/chanalyse/api/v1/signals/summary?window=30d"Python: requests.get("https://qalarc.com/chanalyse/api/v1/signals/gamestop?window=7d").json()
Every signal object carries
| Field | Meaning |
|---|---|
tone_avg | average sentiment, −100 (bearish) … +100 (bullish) |
mention_zscore | how abnormal current volume is vs the entity's baseline |
tone_momentum | recent tone − earlier tone (mood improving/souring) |
tone_dispersion | how contested the mood is (high = a fight) |
buzz_index | 0–100 composite heat (volume z + size + momentum) |
signal | label: bullish_spike / bearish_spike / buzz_spike / warming / cooling / quiet |
confidence | 0–1 (more posters, more buckets, lower dispersion → higher) |
boards, mention_count, category | where it was discussed, how much, and its type |
Live example: /api/v1/signals/bitcoin?window=30d. ⚠️ Imageboard-derived sentiment — noisy, manipulable, not financial advice.