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BFRO Bigfoot

3,659 reports. The most self-exciting dataset we've tested.

Decision Chain: BFRO

Step 1Raw Data Ingestion

Ingest all BFRO reports with day-level timestamps. 3,659 reports spanning decades of field reports.

3,659 reports ingested. Day-level precision.

Step 2Hawkes Process Decomposition

Fit a self-exciting point process. Separates independent (background) from triggered (contagion) events.

Branching ratio 0.988. Half-life 29.9 days. Only 25 of 3,659 reports are independent.

Step 3Data Quality Assessment

Check weather data for heaping and instrument artifacts.

cloud_cover 76% at round numbers (heaping detected). precip_intensity = precip_probability in 51% of rows.

Near-total social contagion

The most self-exciting dataset in the study. 99.3% of Bigfoot reports are triggered by prior reports, with a 29.9-day half-life suggesting month-scale media and word-of-mouth contagion cycles. Only 25 reports out of 3,659 are genuinely independent — people reporting without being prompted by other reports. The weather data has severe quality issues (heaping, copied values) that limit further analysis.