If you’re looking for a good outlet for some computationally-oriented social science work, check out the International Conference on Computational Social Science (). (Disclaimer: I am on the program committee for this conference). Last year, as the Computational Social Science Summit, the conference attracted 200 participants and had a very vibrant set of panels.

Abstracts are due on January 31, 2016. Hoping to see many of you there!

[Note: I do realize that this event was nearly two months ago. I have no one to blame but the academic job market.]

On August 15 and 16, we held the first annual ASA Datathon at the D-Lab at Berkeley. Nearly 25 people came from academia, industry, and government participated during the 24-hour hack session. The datathon focused on open city data and methods, and questions surrounded issues such as gentrification, transit, and urban change.

Two of our sponsors kicked off the event by giving some useful presentations on open city data and visualization tools. Mike Rosengarten from OpenGov presented on OpenGov’s incredibly detailed and descriptive tools for exploring municipal revenues and budgets. And Matt Sundquist from plot.ly showed off the platform’s interactive interface which works across multiple programming environments.

Fueled by various elements of caffeine and great food, six teams hacked away through the night and presented their work on the 16th at the Hilton San Francisco. Our excellent panel of judges picked the three top presentations which stood out the most:

Honorable mention: Spurious Correlations

The Spurious Correlations team developed a statistical definition for gentrification and attempted to define which zip codes had been gentrified by their definition. Curious about those doing the gentrifying, they asked if artists acted as “middle gentrifiers.” While this seemed to correlate in Minneapolis, it didn’t hold for San Francisco.

Second place: Team Vélo 

Team Vélo, as the name implies, was interested in bike thefts in San Francisco and crime in general. They used SFPD data to rate crime risk in each neighborhood and tried to understand which factors may be influencing crime rates, including racial diversity, income, and self-employment.

First place: Best Buddies Bus Brigade

Lastly, our first place winners asked “Does SF public transportation underserve those in low-income communities or without cars?” Using San Francisco transit data, they developed a visualization tool to investigate bus load and how this changes by location, conditional on things like car ownership.

You can check out all the presentations at the datathon’s GitHub page.

Laura Nelson, Laura Norén, and I want to give a special thanks to our sponsors: OpenGov, UC Berkeley Sociology, UW Madison Sociology, the D-Lab, SurveyGizmo, the Data Science Toolkit, Duke Network Analysis Center, plot.ly, orgtheory, Fabio Rojas, Neal Caren, and Pam Oliver.

As ASA gets closer, so does the first ASA Datathon!

We’re on from 1pm August 15 through 1pm the 16th at Berkeley’s D-Lab. Public presentations and judging will take place at one of the ASA conference hotels, the Hilton Union Square, Room 3-4, Fourth Floor from 6:30-8:15 on August 16th.

We’ve got a new website up — asa-datathon.github.io — that’ll be updated as the event approaches. If you haven’t signed up yet, make sure you do!

Signing up will give us a better idea of who will be at the event and how many folks we can expect to feed and caffinate. We’re also going to give teams a week to get to know each other before the event, so signing up will allow us to make sure everyone gets the same amount of time to work.

If you’re interested, you are invited. We don’t discriminate against particular methodologies or backgrounds. We hope to have social scientists, data scientists, computer scientists, municipal staffers, start-up employees, grad students, and data hackers of all stripes – quantitative, qualitative, and the methodologically agnostic.

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