Ma3Map Custom Transit App

Our client for this project, Ma3Route, is a tech startup in Nairobi serving the city's commuters. Their primary service is a collated Twitter feed showing traffic reports submitted by users. With over 500,000 active users, this provides a ton of excellent traffic information for commuters and planners. The problem? Virtually none of it had any location data.

Our solution was to develop a custom stack of technologies that transforms the client's text feed into an interactive map.

How It Works

First, our custom Python code scrapes the tweets in real time. The text is then analyzed through a pre-defined dictionary that locates the tweet based on landmarks mentioned. A second dictionary classifies them by category, and a web app written in Leaflet puts it all together on an interactive map. Travelers and transit planners can then see current problem areas at a glance.

Click here to see the project website in action. Note that the map is real-time, so if it's 3am in Nairobi right now, there might not be much activity.

Tools Used

  • Data Scraping via Twitter API
  • Text Analysis via Python/Pandas
  • Web Mapping via JavaScript/Leaflet
  • Script Timing via PHP