Trump Posts & Context — an observational co-occurrence timeline

A neutral timeline placing Donald Trump's social-media posts alongside contextual inputs (Fox News web-coverage keyword volume, S&P 500 shocks, court events in his own litigation) and policy outputs (presidential documents). It shows what occurred near in time to what — nothing more.

What this is, and what it is not

Posting tempo — Truth Social posts per day

One bar per day = number of posts that day (bucketed in UTC, to match the timeline axis below). Markers overlay market shocks (inputs), scheduled economic releases (inputs, top edge) and presidential documents (outputs) on the same time axis. Descriptive volume only.
Truth Social post Fox News coverage (web) — keyword volume (daily) Market shock ▲ Market shock ▼ Court (Trump litigation) — docket filed Presidential document Economic release (scheduled) Reaction window (visual only)

Posting rhythm — posts by weekday and hour of day

Each cell = total posts in that weekday/hour slot across the whole term, shaded by count. Hour-of-day is bucketed in US Eastern (America/New_York, DST-aware) because time-of-day is only interpretable locally. Descriptive rhythm only — not a measure of state of mind.

Epoch analysis — posting in the hours after an event vs. a random baseline

For each event type, this compares the number of Trump posts in a pre-registered, fixed window of 0 to +6 hours after each event against a baseline in which the same number of events are scattered at random across the term (5,000 permutations). Computed in Python in the pipeline; this page only draws the result.
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Prospective test: jobs-report posting

A single hypothesis, pre-registered on 2026-06-09 (see PREREGISTRATION.md) and computed in Python. Unlike the exploratory analysis above, this one test was fixed in advance, so it is not subject to the multiple-comparisons problem — but it only becomes conclusive once enough future releases have accumulated.
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