networks

Over the course of a month and a half, I had the opportunity to work as a Geospatial Data Analyst (GDA) on a project that applied network theory to the field of Telecommunications. Although this domain was new to me, I quickly became fascinated by network-based approaches to understanding complex systems.

That is why I decided to start this project with a clear and simple goal: to revisit, replicate, and expand upon everything I learned and developed during my time as a GDA, but this time using publicly available or synthetic datasets.

To respect the NDA I signed, this project intentionally explores topics outside the scope of Telecommunications. Instead, I focus on areas that I feel more comfortable working in, and where network theory can offer equally interesting insights: urban mobility, pollution and global trade connectivity.

urban mobility

This first sub-project is all about modelling the public transportation network of Buenos Aires using R.

Bus, subte (underground metro) and trains. Stops of each mean of transport are represented as nodes, while the edges are the routes (weighted by frequency and/or travel time).

I used a Louvain community detection algorithm to identify mobility sub-clusters (this is, zones with tight internal connections but sparse external ones).