Based on an analysis of 4,191,533 flights and 1.3 billion air fares, “in 2013 the best time to buy a domestic airline ticket was 54 days in advance, or 7 1/2 weeks on average.” Check out the related article for other insights.
Facebook analyzed peoples online interactions zeroed around relationship status events. It turns out (not surprisingly I suppose) that relationship changes track closely with online interactions.
and what kind of posts they are interacting with:
Here’s what a breakup looks like:
See where denial of service attacks are occurring based on hourly data. Shows flows as well as relevant news stories. You can scroll along the timeline to view different dates.
Interesting analysis of the composition of Reddit content. Randy Olson has a great blog post about how the chart was created.
Beautiful annotated animation of how gas engines work. Check out the full size version by Jacob O’Neal.
MIT has a fun toy which let’s you conduct network analysis of your gmail emails. There’s a thread over at Slashdot that discusses how this analysis of meta data is similar to the Snowden revealed PRISM project.
How does Google shape its brand through design? Check out their “Visual Assets Guidelines“. It’s all very similar to the flat design movement, but the level of detail is fascinating.
A wonderful interactive timeline of legislation, rulings, and events related to domestic surveillance in the United States. You can drill down into each event for an explanation, and links to primary sources (like the full text of legislation, etc).
While I generally love flat design concepts, Apple really choked on some of the implementation – particularly the icon designs. Check out photos, newstand, game center, and settings below. Barf. They are the way too cluttered busy and abstract – the exact opposite of what they should be.
This has been making the rounds. Based on 150,000 geocoded tweets from June 2012 to April 2013, filtered 1st by use of word, and then manually whether it was used in a negative or derogatory fashion.
Obviously this suffers from selection bias as it only includes people who bother to tweet, and those who aren’t ashamed to do it publicly. There’s also the usual population density distortion (last map below), which would be compounded by cell phone coverage out west. So, basically, this is another pretty visualization of social media meta data that doesn’t really mean much of anything. To be honest I’m surprised they only found 150,000 hateful tweets in 11 months. (The author’s FAQ is an interest read)
An addictive collection of beautiful charts, graphs, maps, and interactive data visualization toys -- on topics from around the world.