Motion designer Patrick Clair tells the story of Stuxnet, "a Microsoft Windows computer worm discovered in July 2010 that targets industrial software and equipment." Unlike many viruses and worms, Stuxnet was designed with a specific target — Siemens Supervisory Control And Data Acquisition (SCADA) systems — and left any other systems unharmed. Stuxnet could then increase pressure in nuclear reactors and turn off oil pipelines, all the while showing monitors everything was fine.

Get the full skinny in Clair's well done motion graphic video below.

[Video link | Thanks, Nigel]

Recommendation site Hunch is another one of those applications that knows a ton of random stuff about its users. In case you've never signed up, you start by answering a bunch of seemingly unrelated questions, and based on your answers, Hunch offers recommendations by correlating your answers with preferences for you and others. This graphic, in collaboration with Column Five Media, shows differences between Mac and PC people within the Hunch community.

Among the findings: Mac people are 95 percent more likely to prefer indie films; PC people are 26 percent more likely to prefer fitting in with others; and as for cable TV networks, Mac people prefer Bravo, HBO, and Showtime, whereas PC people prefer Syfy, History, and USA.

[Hunch | Thanks, @trendyle]

In the most recent media push for Charity: Water, a video of motion graphics explains the importance of clean water and what millions have to go through every day just to get something questionable to drink. Twenty dollars can buy one person access to a safe water source. Kristen Bell narrates.

[Video Link via @JonathanJarvis]

Designer Patrick Smith has a minimalist look at mental disorders:

I was doing some research about mental health and I came across a list of mental disorders. I chose a few, starting with OCD, and set myself the challenge of defining each in a minimal style.

The OCD graphic is definitely the best one of the bunch. Others include agoraphobia, anorexia nervosa, and depression.

[Adapt & Graphic Patrick]

Mozilla tech evangelist Paul Rouget has a go at Internet Explorer 9 in a series of simple graphs, comparing it to Firefox 4. I think Rouget doesn't like IE9. Not sure though.

The obvious progression of this series is to compare Firefox 4 to Chrome and Safari. I await the results.

Continuing their series on world population, National Geographic focuses in on the "most typical" person in the world. The above image is an artist's rendering of the average face computed by the Chinese Academy of Sciences in Beijing. Zoom in and you'll see that the face is made of 7,000 human figures, as shown below. It's true. I counted.

The face is based on photos collected over ten years from several national technology research programs, however, it only seems to be Chinese faces. If that's the case, then obviously it's not really the "face of seven billion." It's also not the world's most typical person. The video below has some similar weird logic.

Okay, wait. I got it. Think of it like this: by "typical" they're referring to mode rather than mean or median. Still though, the feature is better labeled as the face of China. Oh forget it. It is what it is.

[National Geographic | Thanks, Maegan]

Do horoscopes really all just say the same thing? We scraped & analysed 22,000 to see.

See our completed meta-horoscope chart and make up your own mind.

We’ve also created a single meta-prediction out of the most common words..

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How we did it

How do you gather 22,000 horoscopes? Obviously you could manually cut and paste them from one of the many online Zodiac pages. But that, we calculated, would take about a week of solid work (84.44 hours). So we engaged the services of arch-coder Thomas Winnigham to do a bit of hacking.

Yahoo Shine kindly archive their daily predictions in a simple and very hackable format (example). Thank you! So Thomas wrote a Python script to screen-scrape 22,186 horoscopes into a single massive spreadsheet. Screen-scraping is pulling the text off a website after it’s displayed. Python is a programming language. You can use it to write scripts that only gather the specific text you want. Then you run it multiple times so it mines an entire website.

Well, it’s not quite that easy. Big sites like Yahoo have ‘rate-limiting’ on their servers. That means if you access a page too many times too quickly, it thinks you’re a hacker and deploys all kinds of anti-hacking counter-measures. Initially, Thomas set his scraping speed too high (once every 10th of a second) and his IP got instantly banned from Yahoo for 24 hours. After some experimenting (and more bans), he found that a two second delay between scrapes prevented the defense mechanisms from kicking in. The script was set to run in the background (while we smoked cigars and discussed the empire). 12 hours later, we had our 22,000 horoscopes in a single file!

We can’t share the 9.5MB spreadsheet with you because it’s Yahoo’s copyright. But here are the Python scripts should you feel like recreating the experiment.

Filtering it down

So every different type of horoscope got sucked up – career, teen, love, daily overview. Who knew there were so many? It was felt, though, that career & love predictions would have their internal biases i.e. lots of mentions of work, career, love, marriage etc. So we opted to just analyse the generic daily horoscopes for each sign. A total of 4,380 (365 per star sign).

Word Analysis Version 1

We used an online tool called TagCrowd to find the most common words. I prefer it to Wordle. You’ve got better control over any ‘noise’ in the signal, because you can not only filter common words (“and”, “for”, “is” etc) but also a special ‘stoplist’ of words you’ve chosen.

So we broke down the most common 50 words to see if there are any patterns of unique words. This is what was revealed:

You can see the full data in a Google spreadsheet here.

Word Analysis 2

It struck me that several words in the top 50 – like “someone”, “really”, “quite” – were just qualifiers and not really that revealing. You’d find them in any English word analysis.

So we stripped those kinds of words out (see our stoplist). And lo! A fresh set of unique, revealing and more accurate words appeared in the top words per sign.

Can I just say that I have no personal interest in horoscopes. I don’t know what the various characteristics of each star sign are meant to be. So you’ll have to tell me if any of this corresponds to folklore.

This was the data we used to create our meta-chart. Check out the final image. Or see all the data in this Google spreadsheet.

Meta-Prediction

One more thing though. This analysis appears to reveal something. The bulk of the words in horoscopes (at least 90%) are the same. That’s not a full, proper statistical analysis. (If you are a statistician and you want to do a proper analysis, please get in touch)

The cool thing is, once you’ve isolated the most common words, you can actually write a generic, meta prediction that would apply to all star signs, every day of the year. Here it is.

The Future

As ever, I’ve laid out my whole process and all the data here: http://bit.ly/horoscoped.
That way it’s all balanced and you can make up your own mind. Typical Libran!

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In their most recent video (below) to their "State of..." series, JESS3 takes a look at the State of Wikipedia:

The State of Wikipedia not only explores the rich history and inner-workings of the web-based encyclopedia, but it's also a celebration of its 10th anniversary. With more than 17 million articles in over 270 languages, Wikipedia has undoubtedly become one of the most visited and relied upon sites on the web today.

It's really light on the data and kind of fluffy, but Jimmy Wales narrates, so it's worth it to watch just for that. For some reason I expected him to have a grittier voice. It must be the beard.

[State of Wikipedia]

• Visualize This: Winning Wikipedia fundraiser banners
• History of the Iraq War through Wikipedia edits
• Progress: A Graphical Report on the State of the World

Inception was a complex film, so there was understandably some confusion over the levels and who was where. A couple of flowcharts tried to explain, but there was still some debate. So here is the flowchart to trump all other Inception flowcharts. It's by Christopher Nolan himself. Any questions?

[In Contention via Waxy]

• Inception dream levels explained in flowchart
• Another view of Inception, with the kicks this time
• Flowchart Shows You What to Say During Sex

I was listening to writer Clay Shirky talk about cognitive surplus – the idea of spare brainpower in the world’s collective mind just sitting there waiting, wanting, to be harnessed.

He had a stand-out statistic that snagged my mind. I thought I would visualise it.

Shocking proportion. Interestingly, when I sketched the diagram, my imagination had the scale way wrong.