The internet is awash with posts by former PhD students who have succesfully transitioned into data scientist roles in industry (see here, here, here, and tangentially here). I loved reading these posts while studying for job interviews because I felt like the more I saw examples of sucessful transitions, the more likely it seemed that such feats were actually achievable. I am going to try to touch on many of the aspects of leaving academia for data science while trying to limit the length of...| www.ethanrosenthal.com
I think this post will probably conclude my Festival Chatter series on analyzing Bonnaroo tweets in Python (part 1, part 2, part 3). I’ve had a lot of fun messing around with this dataset, but I think it’s time to move on to playing with something else. For this last post, though, I will show some simple sentiment analysis of the collected tweets. There are a whole bunch of issues with this method of sentiment analysis.| www.ethanrosenthal.com
In this series of posts (part 1, part 2), I have been showing how to use Python and other data scientist tools to analyze a collection of tweets related to the 2014 Bonnaroo Music and Arts Festival. So far, the investigation has been limited to summary data of the full dataset. The beauty of Twitter is that it occurs in realtime, so we can now peer into the fourth dimension and learn about these tweets as a function of time.| www.ethanrosenthal.com