Mark’s Bump In’s
Idea
After unexpectedly bumping into three different people from different parts of my life in a single day in NYC, I realized this could be an interesting dataset to track. Inspired by the city’s unique density and interconnectedness, I began logging every bump-in—recording the location, date, nature of the friendship or connection, and how the encounter happened.This dataset is highly subjective, built around my personal experiences and social interactions, reflecting how life in NYC brings people together in unexpected ways.
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Gathering the Data
The dataset is built organically, relying on the serendipity of living in NYC and running into people in various locations. Each encounter is manually logged in a spreadsheet, capturing key details before being converted into a .json file. This data is then processed and visualized using Mapbox, displaying my interactions across the city.
Presenting the Information
The data can be explored in two ways:- Map View – A spatial visualization of where bump-ins occur, revealing frequency patterns across different neighborhoods.
- Timeline View – A chronological breakdown that uncovers trends over time, showing which days of the week and months of the year see the most encounters.
This project transforms casual social interactions into an evolving dataset, offering a playful yet insightful look at the rhythms of personal connections in NYC.
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Development Progress
I started with a basic Mapbox
As the idea evolved, I rebuilt the experience in Bolt.new
Next Steps
I’m continuing to log new encounters and looking for additional ways to surface interesting patterns. A few areas I’m exploring next: