Just because you can topic model something doesn’t mean it actually tells us anything (and please don’t ever describe computational text analysis as “objective”).

One of those afternoons where I’m auditing someone’s analysis code, but it’s an analysis of 4M rows of data, so I’m also doing spurts of grading while I wait for code to execute.

35 GB of data is a lot to begin with, but when it’s 35 GB of CSVs? That’s when it starts to really register.

I got a reminder today that I do the kind of research where something as hilariously unintuitive as telling a program to treat long numbers as “words made up of 0-9” is actually a critical step to making sure you get the right results.

Special thanks to Google Drive for breaking the iframes I’ve been using to set up annotation-enabled readings in Canvas this semester… during the week that students are reviewing readings for their final papers. Really appreciate it.