The Juris Lab is a collaborative empirical legal research blog covering a wide range of subjects, including judicial behavior, regulatory activity, computational linguistics, and litigation analytics. New posts most weekdays.
I have assembled tables of COVID-19 virus data using the daily reports from each state of the United States. From this database of approximately 20,000 entries, I have assembled weekly statistics and rankings for each state. [more inside]
Graphs of the number of posts and comments, the number of unique posters and commenters, and users joining and leaving the site from January 1, 2010 through Jun 15, 2019. I may add some more later if I come up with any other interesting metrics.
Moderators of r/worldnews on reddit worked with me to test an idea: what are the effects of encouraging fact-checking on the response and spread of unreliable news? On average, messages encouraging fact-checking caused a 2x reduction in the reddit score of tabloid submissions, which likely influenced reddit's rankings. [more inside]
The Supreme Court Database is a comprehensive, Creative Commons-licensed database of the decisions of the Supreme Court of the United States, broken down by justices, issues, votes, and numerous other variables. Yesterday marked the newest release, including comprehensive coverage from 1791 through the recently concluded 2015 term. [more inside]
I'm currently taking Harvard Business School's HBX CORe, an online business fundamentals course that covers analytics, accounting, and economics. I'm writing up what I'm learning and making it accessible to non-MBA types. Topics covered include minimum wage, the math behind trendlines, and why the Spiders Georg meme is off, amongst others!
Once upon a time I liberated a bunch of fun post-Civil-War maps, charts and graphs for all to see. But now you can buy them! For your walls! Posters of ye olden days graphics on everything from consumption to population to religion to Germans and more. [more inside]
BEDOPS is a suite of tools to address common questions raised in genomic studies, mostly with regard to overlap and proximity relationships between data sets. BEDOPS aims to be scalable, flexible and performant, facilitating the efficient and accurate analysis and management of large-scale genomic data.