I’ve published issue 062 of my #newsletter covering Fun #DataSets and Falling for #FakeNews: https://t.co/eSoRv6HChk
Interesting Data Sets
With the upcoming elections, there are lots of articles spouting lots of data. These are some interesting data sets that can be used with something like Python’s Pandas library and various visualization libraries like Plotly and D3.
- Kaggle is an interesting place to learn about data science. They have a wide range of neat data sets: https://www.kaggle.com/datasets
HUGE sets of data from the U.S. government: https://www.data.gov/
Pew Research Center’s downloadable datasets: http://www.pewresearch.org/download-datasets/
Propublica’s data store: https://www.propublica.org/datastore/
Falling for Fake News
I came across a really interesting Washington Post article about fake news. The article talks about our human tendency to fall for fake news. While the article traces the origin of a fake video on Facebook, the larger point is how easily we all can fall for fake news/photos/videos. The problem is that we are not very good at telling fake media from real media, while the technology to produce fake information has significantly increased in sophistication and ease of use. This particular paragraph from the article is quite telling:
Even after decades of Photoshop and CG films, most of us are still not very good about challenging the authenticity of images — or telling the real from the fake. That includes me: In an online test made by software maker Autodesk called Fake or Foto, I correctly identified the authenticity of just 22 percent of their images. (You can test yourself here.)
I took the Autodesk fake photo test, and I also got 22 percent of the images correct. I’m stunned by this – I got one out of every four pictures correctly. How does this apply to read articles and posts on the web (not just Facebook but all other sources of information on the web)?
I’ve been struggling to figure out how to deal with this. With the upcoming U.S. midterm elections on November 6th, I wonder about this even more. The only thing I can come up with is the Russian proverb “Trust but verify”. If I want to trust a particularly new story, then I am obligated to verify its authenticity by checking other news sources such as actual newspaper sites with differing viewpoints (right, left, and middle). The obligation is on me to put the effort and investigate a news item that on first glance seems super-compelling and utterly true. In fact, the truer a news item feels, the more suspicious I need to become and the more verification it requires.
Yellow journalism is nothing new, but the rapid application of technology to make the news seem authentic is the biggest difference from the past.
“The Second Ship (The Rho Agenda Book 1)”: I got this Richard Phillips recommendation from Steve Gibson’s science fiction reading guide (see the top link on https://www.grc.com/linkfarm.htm). It initially felt a little bit too YA, but then it took off like a rocket. It’s fun well-written scifi. A fun sentence from the book:
Fresh snow was fun and could sometimes get you an extra day off. Old snow made you feel as gray and dirty as it was.
Thoughts? Feedback? Let me know: @eli4d on Twitter
Excellent episode about the happenings in @elmlang world (@rtfeldman’s enthusiasm for #ElmLang is infections…in a good way of course 😺)
The @changelog: episode 319 – Keepin’ Up with #Elm with Richard Feldman – https://t.co/MzL0NGDNX1