News-feed attention from listing day to the latest reading: counts, concentration, and the trailing week
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-10-05, from SPCX: SpaceX Stock Price Decline From Peak.
- Rows × columns
- 1 × 14
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
total_articles |
number | every row is 754 | |
publishers |
number | every row is 5 | |
top_publisher |
text | 1 distinct value (The Motley Fool) | |
top_publisher_share_pct |
number | every row is 82.9 | percent |
busiest_month |
number | every row is 6 | |
busiest_dom |
number | every row is 12 | |
ipo_day_articles |
number | every row is 42 | |
peak_session_articles |
number | every row is 31 | |
max_daily_after_peak |
number | every row is 29 | |
ipo_day_minus_max_after |
number | every row is 13 | |
first_week_avg |
number | every row is 25.7 | |
last7_avg |
number | every row is 3.3 | |
tsla_co_tagged |
number | every row is 145 | |
nasdaq_titled |
number | every row is 33 |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
Run it yourself
This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.
WITH daily_counts AS (
SELECT toDate(toTimeZone(published_utc, 'America/New_York')) AS d, count() AS n
FROM global_markets.stocks_news
WHERE has(tickers, 'SPCX')
AND published_utc >= toDateTime('2026-06-12 04:00:00') AND published_utc < now()
GROUP BY d
),
top_pub AS (
SELECT JSONExtractString(publisher, 'name') AS p, count() AS n
FROM global_markets.stocks_news
WHERE has(tickers, 'SPCX')
AND published_utc >= toDateTime('2026-06-12 04:00:00') AND published_utc < now()
GROUP BY p ORDER BY n DESC, p ASC LIMIT 1
)
SELECT
count() AS total_articles,
uniqExact(JSONExtractString(publisher, 'name')) AS publishers,
(SELECT p FROM top_pub) AS top_publisher,
round(100.0 * (SELECT n FROM top_pub) / count(), 1) AS top_publisher_share_pct,
(SELECT toMonth(argMax(d, (n, -toInt32(toDayOfYear(d))))) FROM daily_counts) AS busiest_month,
(SELECT toDayOfMonth(argMax(d, (n, -toInt32(toDayOfYear(d))))) FROM daily_counts) AS busiest_dom,
countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-06-12')) AS ipo_day_articles,
countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-06-16')) AS peak_session_articles,
(SELECT max(n) FROM daily_counts WHERE d > toDate('2026-06-16')) AS max_daily_after_peak,
countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-06-12')) - (SELECT max(n) FROM daily_counts WHERE d > toDate('2026-06-16')) AS ipo_day_minus_max_after,
(SELECT round(sum(n) / 7, 1) FROM daily_counts WHERE d <= toDate('2026-06-18')) AS first_week_avg,
(SELECT round(sum(n) / 7, 1) FROM daily_counts WHERE d > today() - 7) AS last7_avg,
countIf(has(tickers, 'TSLA')) AS tsla_co_tagged,
countIf(positionCaseInsensitive(title, 'nasdaq') > 0) AS nasdaq_titled
FROM global_markets.stocks_news
WHERE has(tickers, 'SPCX')
AND published_utc >= toDateTime('2026-06-12 04:00:00') AND published_utc < now()
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