The rise and fall of American Hallowe'en costumes


A clever, interactive chart from NPR's Planet Money tracks the relative popularity of different American Hallowe'en costumes over the past five years.

Zombies Are Hot, But Clowns Are Not [Planet Money/NPR]

(via Kottke)

Who is Gamergate? Analysis of 316K tweets


Waxy took a deep three-day sample of #Gamergate-tagged tweets and did some great analysis to uncover the composition and patterns of participants on both sides of the debate.

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Distribution of letters in parts of English words


Prooffreader graphed the distribution of letters towards the beginning, middle and end of English words, using a variety of corpora, finding both some obvious truths and some surprising ones. As soon as I saw this, I began to think of the ways that you could use it to design word games -- everything from improved Boggle dice to automated Hangman strategies to altogether new games.

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Cognitive Bias Parade: CC-licensed collage illustrations of predictable irrationality

James Gill writes, "Cognitive Bias Parade is a site that takes a daily look at deviations in judgement and reconstructed realities. It is an illustrated review of the many ways the brain has evolved to lie to itself. It is not simply meant to scold. The spirit of the project was captured once in a quote by the magician Jerry Andrus: 'I can fool you because you're a human. You have a wonderful human mind that works no different from my human mind. Usually when we're fooled, the mind hasn't made a mistake. It's come to the wrong conclusion for the right reason.'

"I've given a Creative Commons Share-Alike status to my work on the site. I ask only that a link-back be given for my website as credit."

(Above: Observation selection bias... The effect of suddenly noticing things that were not noticed previously – and as a result wrongly assuming that the frequency has increased.)

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Visualizing inspiring quotes about privacy


Kevin writes, "With the Privacy is a right project I try to visualize the global privacy debate by using quotes on the subject and turn them into large (in real life) visuals. I started out with key figures in this debate (such as Edward Snowden, Kirsty Hughes and even Cory Doctorow) but now everyone can react and share their view on the subject by submitting a quote on the site. Any inspiring quote will then be turned into art by me. Some of the visuals will be part of my graduation exposition (25th - 29th of June) for the Willem de Kooning Rotterdam University of Applied Sciences in Rotterdam, the Netherlands."

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De-obfuscating Big Cable's numbers: investment flat since 2000


The cable lobby group NCTA claims the industry has been investing record amounts in network upgrades, which will dry up if they are forced to endure Net Neutrality. Techdirt points out that Big Cable's numbers are cumulative, and re-runs them year on year. Turns out investment has been flat since about 2000.

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Now: XKCD helps you visualize the time of day all over the world


In Now, the latest XKCD cartoon, Randall Munroe provides a handy, continuously updated way to visualize the current time all over the world. I happen to know that Munroe is an inveterate long-distance driver who likes to pass the hours on the road by calling friends; I imagine that a wheel like this would be handy for helping him figure out which continent he should be searching for in his address-book in order to find conversational partners at any hour of day.

XKCD: Now

Data visualization shows US isolation in pushing for brutal Trans-Pacific Partnership


Gabriel Michael, a PhD candidate at George Washington University, subjected the IP Chapter of the secret Trans-Pacific Partnership, leaked by Wikileaks last week to statistical analysis. The leaked draft has extensive footnotes indicating each country's negotiating positions. By analyzing the frequency with which the US appears as the sole objector to other nations' positions, and when the US is the sole proponent of clauses to which other nations object, Michael was able to show that TPP really is an American-run show pushing an American agenda, not a multilateral trade deal being negotiated to everyone's mutual benefit. Though Canada is also one of the main belligerents, with even more unilateral positions than the USA.

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Enormous timescales made graspable by graphs

Wait But Why has a fantastic series of graphs that aim to help us wrap our heads around the enormous timescales on which forces like history, biology, geography and astronomy operate. By carefully building up graphs that show the relationship between longer and longer timescales, the series provides a moment's worth of emotional understanding of the otherwise incomprehensible.

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Maps of corporate tax-avoidance hairballs


OpenCorporates has a data-visualization tool for peering into the corporate tax-evasion structures of big corporations -- subsidiaries nested like Russian dolls made from Klein bottles:

In Hong Kong, there's a company called Goldman Sachs Structured Products (Asia) Limited. It's controlled by another company called Goldman Sachs (Asia) Finance, registered in Mauritius.

That's controlled by a company in Hong Kong, which is controlled by a company in New York, which is controlled by a company in Delaware, and that company is controlled by another company in Delaware called GS Holdings (Delaware) L.L.C. II.

...Which itself is a subsidiary of the only Goldman you're likely to have heard of, The Goldman Sachs Group in New York City.

That's only one of hundreds of such chains. All told, Goldman Sachs consists of more than 4000 separate corporate entities all over the world, some of which are around ten layers of control below the New York HQ.

Of those companies approximately a third are registered in nations that might be described as tax havens.Indeed, in the world of Goldman Sachs, the Cayman Islands are bigger than South America, and Mauritius is bigger than Africa.

Tim Harford's 2011 book Adapt proposes an ingenious regulatory solution to this problem, explaining how it might have been applied to companies like Lehman, whose complex structures drew out the post-bankruptcy mess for years and years. He suggested that if banks were stress-tested to determine how long they'd take to sort out after a bankruptcy, and then required to keep reserve capital necessary to run all operations through that whole period, they would be strongly incentivized to have the most simple, transparent corporate structures. Otherwise, they'd have to tie up billions of dollars in escrow to keep the doors open in the event that it all collapsed.

OpenCorporates | How complex are corporate structures? (via JWZ)

Realtime map of anonymous edits to Wikipedia


Stephen LaPorte and Mahmoud Hashemi's "Wikipedia Recent Changes Map" plots anonymous edits to Wikipedia on a world-map in realtime, based on the location of the user (only anonymous users are identified by IP address, so they're the only ones whose locations can be estimated). It's a hypnotic view into Wikipedia's casual users and vandals, as well as unobservant users like (I often forget that I'm logged out until after my edit, and have to go back and add an attribution).

When an unregistered user makes a contribution to Wikipedia, he or she is identified by his or her IP address. These IP addresses are translated to the contributor’s approximate geographic location. A study by Fabian Kaelin in 2011 noted that unregistered users make approximately 20% of the edits on English Wikipedia [edit: likely closer to 15%, according to more recent statistics], so Wikipedia’s stream of recent changes includes many other edits that are not shown on this map.

You may see some users add non-productive or disruptive content to Wikipedia. A survey in 2007 indicated that unregistered users are less likely to make productive edits to the encyclopedia. Do not fear: improper edits can be removed or corrected by other users, including you!

This map listens to live feeds of Wikipedia revisions, broadcast using wikimon. We built the map using a few nice libraries and services, including d3, DataMaps, and freegeoip.net. This project was inspired by WikipediaVision’s (almost) real-time edit visualization.

Wikipedia Recent Changes Map

Census Dotmap: a dot for every person in the United States

Cartography and data analysis nut Brandon M-Anderson put together this impressive zoomable map of the United States with one dot for each of the 308,450,225 people recorded by the 2010 census: oddities revealed include people living in "abandoned" areas or parks. A Redditor stitched the tiles into a huge image.

Dataviz for "My Ideal Bookshelf"


Fred sez, "My lady, Thessaly La Force, recently published a book with the artist Jane Mount called 'My Ideal Bookshelf.' In it, Thessaly interviews over 100 people and Jane paints their bookshelves. As I observed Jane and Thessaly compile the book over the last year, I couldn't help but think about all the fun opportunities I could have exploring the data behind the shelves. Each of the 101 contributors Thessaly interviewed picked as many books as they thought represented their ideal bookshelf, and I knew some of them would pick identical books. What would the most popular book be (it was Lolita)? On average, how many books did people choose? What would a taste graph linking contributors to each other using the books on their shelves look like? So I pulled the data together into a set of graphs an interactive 3D plot that visualizes the relationships of the contributors based on the books they choose."

The Data Behind My Ideal Bookshelf (Thanks, Fred!)

Silcon Valley's high-tech bus commuter lines visualized

Stamen, a design firm in San Francisco, was commissioned to study the private transport networks that run from San Francisco down to Silicon Valley. The traditional commuter dynamic for cities is suburbanites coming into the city to work, but in San Francisco it runs both ways, as city-dwelling tech workers catch a variety of semi-luxurious, WiFi-equipped buses with power outlets and work tables to tech campuses down the peninsula. I watched this with some amusement when I was in San Francisco this summer, observing how a crowd of googlers with Android handsets would magically converge on a corner near Dolores Park just as a big black Google bus pulled up and whisked them away (A friend at Google tells me that his bus has its own mailing list where they recently had a kerfuffle when some enthusiastic people proposed a weekly festive party-ride on Friday afternoons, to the horror of the more sedate riders).

Fun fact: apparently Twitter employees refer to the entire Mission district as "the campus" (though I assume that this is ironic).

We enlisted people to go to stops, measure traffic and count people getting off and on and we hired bike messengers to see where the buses went. The cyclists used Field Papers to transcribe the various routes and what they found out, which we recompiled back into a database of trips, stops, companies and frequency. At a rough estimate, these shuttles transport about 35% of the amount of passengers Caltrain moves each day. Google alone runs about 150 trips daily, all over the city.

We wanted to simplify that, to start thinking about it as a system rather than a bunch of buses, so we began paring down the number of stops by grouping clusters where the stops were close to each other.

The subway map is the end result of that simplification; it's not a literal representation, but it's much more readable than the actual routes. We also wanted to show the relative volumes, so the map segments are scaled by how many trips pass through them; you get a sense for just how much traffic the highways get, and how the routes branch out from there to cover the city. We only mapped San Francisco shuttles, many of these companies operate additional routes in East Bay, the Pennensula, and around San Jose, including direct routes from Caltrain stations to corporate campuses.

The work was commissioned by ZERO1 and partly funded by the James Irvine Foundation.

The City from the Valley (2012) (Thanks, Fipi Lele!)

London mapped by common surnames


James Cheshire (Department of Geography, UCL) produced a series of interactive maps of London that show the relationship of common surnames to different neighbourhoods:

This map shows the 15 most frequent surnames in each Middle Super Output Area (MSOA) across Greater London. The colours represent the origin of the surname (*not necessarily* the person) derived from UCL’s Onomap Classification tool. The surnames have also been scaled by their total frequency in each MSOA.

London Names (via Sociological Images)