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See Inside April 2011

Getting to Know You: Bit.ly Chief Scientist Finds Rich Data in Shortened Links

The brain behind many of the shortened URLs on the Web talks about data analysis and how it lets her figure out which soccer team won without watching the match



Pınar Ózger

Name: Hilary Mason
Title: Chief scientist, bit.ly
Location: New York City

I joined bit.ly as chief scientist in October of 2009. The company is a URL-shortener and content-sharing platform; we provide tools for people to share and track links on the Internet.

People might not imagine that there are scientists working at Internet start-ups, but bit.ly was a bit ahead of the trend of recognizing the value of data. Approximately one third of my day is spent doing pure research—looking at data about what people click on, trying to figure out what it says about human behavior and communication. I look for interesting events, trends or visualizations. During the World Cup, for example, we could determine what two teams were playing and what team won without even watching the game—during the games the people in the two competing countries would be clicking on soccer links. After the game, though, the people in the winning country would continue to click soccer links while the people in the losing country would not.

The other two thirds of my day I focus on translating models and equations into functional systems. Re­cently we built a program that takes a link you’re interested in and spits back similar links. It’s great for finding different perspectives on the same topic. In our current project we’re developing a social newsreader that learns your interests and recommends links in real time. After that, we’d like to provide contextually aware information. So if you’re a pizza lover in New York City, we’d let you know right away if a famous pizza place nearby is having a special.

After graduate school, I joined Johnson & Wales University in Rhode Island as an assistant professor, but I continued to program in addition to teaching and working on research. I built a program that crawled job boards to determine which skills employers value, which helped Johnson & Wales explore ways to improve its curriculum.

Projects like that made me realize that I wanted mainly to code and build useful things, so I left teaching.

I’m really curious about people—what their desires and interests are—and bit.ly’s data tell me that. It gives me an unprecedented window into human communication and behavior.

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