Derek Willis

I first need to apologize to and thank a guy named Chuck Morris.

I began collecting congressional press releases more than a dozen years ago for the reasons I usually start collecting anything: I was interested in them and there wasn’t a freely-available dataset I could find.

Of nearly all of the potential uses for Large Language Models, perhaps the best and most defensible is using them to write code.

Today I’m releasing two datasets on women’s college basketball, one an update and the other a brand new collection, both tied to the 2025-26 season.

A few years ago I started publishing roster data for women’s college basketball, thanks to the assistance of students in my Sports Data Analysis and Visualization class at Maryland.

When I started teaching at Maryland in 2021, one of the first things I did was pull up the university’s Schedule of Classes, something I still do all the time.

Today I’m releasing a new Python command-line library that allows users to ask questions of federal campaign finance filings by leveraging large language models, with some built-in help.

In the 12-plus years that we’ve been turning official precinct election results into data at OpenElections, the single biggest problem has been converting pictures of results into CSV files.

As the students drifted away from the Zoom call one-by-one, one young woman stuck around.

The first thing you should know about me is that I’ve been programming computers for at least two decades.

I had been staring at my Political Email Extraction Leaderboard since I first published it, and was disappointed by some of the performances I found in extracting committee names from the disclaimers in fundraising messages.

As a former Hill reporter, some of the best never-published stories revolved around the treatment (usually, mistreatment) of congressional staff.

What kind of sicko signs up for political fundraising emails from just about every committee?

The following is based on a talk I gave at American University on Oct. 25, 2024.

Whenever American federal officials - from the President to members of Congress and executive branch employees - meet with foreign government representatives, they often are offered gifts.

If there’s anything that I’ve developed an expertise in in the past 25 years, it’s campaign finance data.

I called it my “running with scissors” class, because after I offered to teach a course on using artificial intelligence for journalism, the thought dawned on me that I had very little idea how to actually design and teach such a class.

When it comes to turning official precinct election results into data, there are few states like Mississippi.

Last year some students of mine at Maryland and I worked to produce a comprehensive set of data on women’s college basketball rosters, and while that process involved a lot of manual effort on top of a base of Python scrapers, it also got me thinking: how…

If there’s one state that justifies the need for OpenElections, it’s Mississippi.