Instagram Geo-Tags Used to Map a Stalker's Surveillance Pattern

Background

A client reported a growing sense of being followed. They suspected a specific individual — an ex-partner — but had no concrete proof. Police required evidence before acting.

Investigation Methodology

1. Geotag Timeline Analysis: We extracted geolocation data from every public Instagram post and story by the suspected stalker over a 6-month period.
2. Proximity Correlation: The stalker's geolocation data was mapped against the client's known daily routine (workplace, gym, grocery store, etc.).
3. Frequency Analysis: We calculated the statistical probability that the observed proximity patterns were coincidental.

Key Findings

• Over a 6-month period, the suspected stalker posted content from locations within 200 meters of the client's known locations 47 times.
• The probability of this overlap occurring randomly was less than 0.001%, based on venue density and city population models.
• The stalker's posting times at these locations consistently fell within the windows when the client would typically be present.

Outcome

The statistical analysis and geolocation evidence were compiled into a forensic report that met the evidentiary standard for a stalking complaint. A restraining order was granted. Total investigation time: 2 weeks.