Last August, I released an XML copy of the Michigan Compiled Laws (MCL). As an example of what could be done with the structured data, I also created a single-page HTML version generated from the XML. Since then, there's been significant activity in the state statutory arena; my favorite example is Virginia Decoded, a
Where would you go to find out what the longest bill of the 112th Congress was by number of sections (H. R. 1473)? How about by number of unique words (H.R. 3671)? What about by Flesch-Kincaid reading level (S. 475)? Head on over to this table of bills, updated daily for the 112th
Last night, I posted a copy of the Michigan Compiled Law (MCL) as an improved and structured XML document. As an example of what can be easily done with freely available, structured, machine-readable law, I've produced a single HTML file containing the entire MCL with table of contents, internal hyperlinks, and indentation. You can either
A few weeks ago, Ari Hershowitz posted on Quroa calling for a Californa code hackathon. Since Ari was drumming up support for software developers to build state-level tools, I thought I'd see what data the Michigan government had to offer. However, Michigan, unlike California, does not provide any bulk access to its Code. Access to Michigan
I've been busy lately with my new day job and wedding planning , but Dan and I still managed to meet two big goals in the past week. First, we've finalized a stable version of the Electronic World Treaty Index. This is a big deal in the world of international relations and international law,
Later this month, I'll be giving a keynote at a meeting on Law and Computation at the University of Houston. As part of the talk, I'm putting together an example of how I think machine learning and structured data can help build a better legal search engine. For the talk, I'll be building a subset
Last week, I posted some R code that downloads the user and timestamp of tweets that contain a given hashtag going back as far as Twitter search will allow. As I noted in the post, the text of these tweets isn’t stored because of encoding issues with R and its JSON packages. A few people emailed asking
I've been playing with Twitter data over the last week, archiving Algerian, Egyptian, Iranian, and Chinese tweets. I thought I'd bring the story a little closer to home this time by archiving tweets from Wisconsin Union protesters on the #wiunion tag. Grab the dataset of 165,593 tweets here, and check out the two figure
I’ve posted three examples of Twitter hashtags datasets in the last week: one on China, one on Iran, and one on Algeria. In order to build these datasets, I needed to obtain older tweets; this is slightly more difficult than simply filtering the streaming feed for your hashtag of choice. The original code I wrote
Earlier this week, I posted a ~100k tweet dataset on the #25bahman protests in Iran. The corresponding figure of frequencies showed a strong presence on Twitter, with over 500 tweets per 5 minute period at peak. You can download the dataset or check out the figure in that post. I decided to take a quick
