Few things are as controversial in these perilous times as Donald Trump’s Twitter account, often laced with derogatory language, hateful invective, and fifth-grade name-calling. But not all of Trump’s tweets sound like they came straight out of a dystopian dictator’s mouth. Some of them are actually nice.

Probably because he didn’t write them.

Join us on a discerning journey as two data scientists tackle Donald Trump’s Twitter account and, through quantitative methods, reveal to us which hands are behind the tweets.

Episode Transcript

For the full episode, listen by selecting the Play button above or by selecting this link, or you can also listen to the podcast through Apple PodcastsGoogle PlayStitcherand Overcast.

Dave Robinson: So the original Trump analysis is certainly the most popular blog post I’ve ever written. It got more than half a million hits in the first week and it still gets visits . . . and the post still gets a number of visits each week. I was able to write it up for the Washington Post and was interviewed by NPR.

Ginette: “I’m Ginette.”

Curtis: “And I’m Curtis.”

Ginette: “And you are listening to Data Crunch.”

Curtis: “A podcast about how data and prediction shape our world.”

Ginette: “A Vault Analytics production.”

Curtis: Here at Data Crunch, as we research how data and machine learning are changing things, we’re noticing an explosion of real-world applications of artificial intelligence that are changing how people work and live today. We see new applications every single day as we research, and we realize we can’t possibly keep you well enough informed with just our podcast. At the same time, we think it’s really important that people understand the impact machine learning is having on our world, because it’s changing and is going to change nearly every industry. So to help keep our listeners informed, we’ve started collecting and categorizing all of the artificial intelligence applications we see in our daily research. These are all available on a website we just launched, which Data Elixir recently recognized as a recommended website for their readers to check out. The website includes, for example, a drone taxi that will one day autonomously fly you to work, a prosthetic arm that uses AI to aid a disabled pianist to play again, and a pocket-sized ultrasound that uses AI to detect cancer.

Go explore the future at datacrunchpodcast.com/ai, and if you want to keep up with the artificial intelligence beat, we send out a weekly newsletter highlighting the top 3-4 applications we find each week that you can sign up for on the website. It’s an easy read, we really enjoy writing it, and we hope you’ll enjoy reading. And now let’s get back to today’s podcast.

Ginette: Today, we’re chatting with someone who made waves over a year ago with a study he conducted and he recently did a follow up study that we’ll hear about. Here’s Dave Robinson.

Dave: I’m a data scientist at Stack Overflow, we’re a programming question-and-answer website, and I help analyze data and build machine learning features to help get developers answers to their questions and help them move their career forward, and I came from originally an academic background where I was doing research in computational biology, and after my PhD I was really interested in what other kinds of data I could apply a combination of statistics and data analysis and computer programming too.

Curtis: Dave studied stats at Harvard and then went on to get his PhD in Quantitative and Computational Biology from Princeton. He did a study on Donald Trump’s tweets in 2016 you may have heard about and posted it to his blog, Variance Explained.

For the full episode, listen by selecting the Play button above or by selecting this link, or you can also listen to the podcast through Apple PodcastsGoogle PlayStitcher, and Overcast.


Picture Source

Photo by Kayla Velasquez on Unsplash


“Night Owl” by Broke For Free is licensed under a Creative Commons Attribution License