More than a million people have now used our Wolfram|Alpha Personal Analytics for Facebook. And as part of our latest update, in addition to collecting some anonymized statistics, we launched a Data Donor program that allows people to contribute detailed data to us for research purposes.
A few weeks ago we decided to start analyzing all this data. And I have to say that if nothing else it’s been a terrific example of the power of Mathematica and the Wolfram Language for doing data science. (It’ll also be good fodder for the Data Science course I’m starting to create.)
There’s a whole lot of data showing that gender is one of the strongest sources of real, actual measurable differences between human beings. Versus race, religion, culture, language etc… these things are noise compared to vast gender differences. But it’s interesting to see some strong overlaps here as well.
Without a scale, or even axis labels, aren’t these graphs rather useless, since a viewer can’t tell what they’re supposed to represent and what the information is?
Maybe it’s because we’re not in school, mostly figured out our work, got our long-term housing, kids are out of the house (or nearly), seen the ups and downs of our favorite sports teams, now adding only a few new musical interests or tech items in a given year, and we’re smart enough to know not to spend a lot of time on things like fashion and TV shows. So what’s left? Politics, health, family, and the weather.
The retired people I know all are busier than many people in their 20s and 30s. In fact, come to think of it, nearly all of the people I know in their 70s, 80s and even 90s are still working.
Are you quite sure you know the ages of the people you’re “sparring” with online?
