A couple weeks ago, my good friend Max Chafkin and I took a quasi-scientific look at three decades-worth of National Magazine Award-winning feature stories. How many had nut graphs? How many had swear words? Is it possible to use data to predict 2016's winner?
Thankfully, our prediction didn't come true (Kathryn Schulz won for The Really Big One). If it were so easy to pick a feature writing winner based on word count, swear words, and whether the story begins with an anecdotal lede, honestly I think I'd feel kind of depressed. Still, it was fun looking at whether masterful stories followed or disregarded various magazine conventions. I hope you enjoyed it.
Also, I ended up with a nice database of all the stories nominated for an ASME. If you've got other data-related questions, let me know and I'll try to take a look. I might post other stray observations about data and writing here in the future, too. Also—I'm deeply interested in learning more about how to do real data journalism. If you have any advice or ideas for me, please reach out.