🧠 Reframing Networking: A Data-Driven Experiment
Networking advice often feels vague: “Just put yourself out there!” or “Talk to the right people!” But… who exactly are the right people? Instead of relying on gut feelings or LinkedIn stalking, I wanted to approach this question logically.
This project reframes the typical question — “Who do I network with?” — into a more strategic one: “Who should I network with?”
Using the structure of a corporate hierarchy (where each person has a title and a manager), I applied four centrality measures from network theory — degree, betweenness, closeness, and eigenvector — to give each individual a numerical score representing their position within the social hierarchy of the organization. Or to put it more bluntly: a data-backed sense of how important someone is in the grand org chart of life (corporate life, at least).
The goal isn’t to gamify your career (okay, maybe just a little), but to offer a logical, fun framework for thinking differently about how we navigate professional relationships.
If you want to learn how you can improve your eigenvector centrality score and be the envy of your colleagues – Check out the project below.
This is just the starting point… next, I’ll add a slight twist: simulating what happens when someone new enters your network. For example — using our fictitious company, Backdoor Strategies, Inc. — what would happen if our humble Analyst Donny managed to build a relationship with the company President?
Would schmoozing with the execs boost his visibility in the company’s network? Stay tune for Part 2.
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