Researchers build SnapScope to scrape Snap Map at city scale
515K public snaps collected in 23 days with 94.8% duplication rate
Researchers from Saudi Arabia have developed SnapScope, an open-source platform designed to scrape and analyze public Snap Map data at unprecedented city scale. The system combines a back-end collection pipeline with a web-based front end for interactive data exploration, side-by-side neighborhood comparison, and data export. In a real-world deployment over Riyadh, the team collected 515,364 unique public snaps across 23 days using a 1km grid with 2,740 query points.
The platform addresses a critical gap: Snapchat's Snap Map lacks a public API, and no prior tools existed for reproducible city-scale collection. A saturation test revealed that 94.8% of returned observations were duplicates, highlighting data redundancy challenges. The researchers provide a privacy-safe aggregate dataset under CC BY 4.0 and emphasize that SnapScope is city-agnostic, redeployable by simply substituting grid coordinates and boundary polygons for any urban area.
- SnapScope collected 515,364 public snaps in Riyadh over 23 days using 2,740 query points on a 1km grid
- 94.8% of collected data were duplicates, revealing Snap Map's data redundancy issues
- Open-source release under CC BY 4.0 includes privacy-safe aggregate dataset and interactive exploration tools
Why It Matters
Enables researchers and urban planners to analyze public social media data at city scale while respecting privacy boundaries