Understanding the Reaction to Amazon Prime Air (Or: Tapping Twitter’s Firehose for Fun and Profit with pandas)
On Cyber Monday eve, Jeff Bezos appeared in a 60 Minutes segment and revealed to the world that he’s been working on an experimental effort called Amazon Prime Air. The general idea behind Amazon Prime Air is that Amazon may one day deliver relatively lightweight items directly to your doorstep in less than 30 minutes after you order via a fleet of small unmanned aerial vehicles. The following short video summarizes the concept in case you’ve somehow missed it.
Within moments of the announcement, I tapped Twitter’s firehose for the keyword query “Amazon” by employing a couple of recipes from the Twitter Cookbook, because this seemed like an ideal opportunity to capture a relatively large volume of tweets laden with emotional reaction. Over the course of the next few hours, I collected ~125,000 tweets, analyzed them in IPython Notebook with pandas, and later presented these findings as an online mini-workshop. (A video archive of the entire workshop is now available in case you missed it last week.)
Rather than rehashing the results here, I’d rather invite you to spend a few minutes reviewing the notebook. It’s easy to follow along with, features lots of narrative, and includes output from running the code. The analysis techniques range from basic times-series analysis with pandas to rudimentary natural language processing toward the end, so there should be a little something in there for everyone.
As always, questions and comments are welcome. Enjoy.