There is an allure to a Magic 8 Ball. You roll the thing in your hands, you ask it a question, and—presto!—you have an answer. The whole thing is wonderfully simple. The only problem—and it’s a big problem—is that it’s random. Can you really rely on the Magic 8 Ball’s advice? My sources say no.
I’ve long wished, however, that there could be something similar—a Rational 8 Ball or some such—for big life decisions.
Now there is. Or, at least: There’s something that claims to be.
Read more. [Image: Flickr/CRASH:candy]
In his 1987 book The Secret Museum, Walter Kendrick explored the many ways that technology transforms pornography. Technological innovations—the advent of the printing press, the rise of the home video camera, the widespread adoption of the VCR—changed the way, he argued, that people related to sex as a media product. And the Internet, of course, has continued that evolution, expanding and democratizing pornography in ways that the Marquis de Sade, not to mention Hugh Hefner, could never have imagined.
In a recent paper, the team at Sexualitics, an interdisciplinary collaboration among sociologists, political scientists, and statisticians, attempted to quantify those transformations—through what they call “a quantitative analysis of online pornography.” The team looked at (“looked at,” to be clear, in the most scientific sense) videos uploaded to the porn site Xhamster between 2007 and February 2013. There were around 800,000 of them. They then extracted key words (I’ll let you guess! Though, if you don’t mind a literary strain of NSFW, you can also see a selection on page 11, here) from the titles of those productions.
The Weather Company’s Vikram Somaya talks about why marketers are clamoring for weather data.
Read more. [Image: Michael Myers]
In 2003, thanks to Michael Lewis and his best seller Moneyball, the general manager of the Oakland A’s, Billy Beane, became a star. The previous year, Beane had turned his back on his scouts and had instead entrusted player-acquisition decisions to mathematical models developed by a young, Harvard-trained statistical wizard on his staff. What happened next has become baseball lore. The A’s, a small-market team with a paltry budget, ripped off the longest winning streak in American League history and rolled up 103 wins for the season. Only the mighty Yankees, who had spent three times as much on player salaries, won as many games. The team’s success, in turn, launched a revolution. In the years that followed, team after team began to use detailed predictive models to assess players’ potential and monetary value, and the early adopters, by and large, gained a measurable competitive edge over their more hidebound peers.
That’s the story as most of us know it. But it is incomplete. What would seem at first glance to be nothing but a memorable tale about baseball may turn out to be the opening chapter of a much larger story about jobs. Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed.
Yes, unavoidably, big data. As a piece of business jargon, and even more so as an invocation of coming disruption, the term has quickly grown tiresome. But there is no denying the vast increase in the range and depth of information that’s routinely captured about how we behave, and the new kinds of analysis that this enables. By one estimate, more than 98 percent of the world’s information is now stored digitally, and the volume of that data has quadrupled since 2007. Ordinary people at work and at home generate much of this data, by sending e-mails, browsing the Internet, using social media, working on crowd-sourced projects, and more—and in doing so they have unwittingly helped launch a grand new societal project. “We are in the midst of a great infrastructure project that in some ways rivals those of the past, from Roman aqueducts to the Enlightenment’s Encyclopédie,” write Viktor Mayer-Schönberger and Kenneth Cukier in their recent book, Big Data: A Revolution That Will Transform How We Live, Work, and Think. “The project is datafication. Like those other infrastructural advances, it will bring about fundamental changes to society.”
Read more. [Image: Peter Yang]
[Images: Market Watch]
Visualizing the Occupy Wall Street protests:
Mother Jones has put together this Occupy Wall Street map they continue to update and they’re are asking readers to submit new locations or news stories associated with the protests. They also have an excellent run down of how the Occupy Wallstreet is utilizing social media, along with charts, stats and ongoing coverage.
The Atlantic has a powerful photo gallery of the protests beyond New York, spanning from LA to Boston.
Have to keep changing the zoom level on our Occupy Wall Street map—news reports say protests have spread to Anchorage, Hilo, Hawaii, several cities in Canada, and now Melbourne.
The Revolutions Were Tweeted — an stunning visualization of information flows on Twitter during the 2011 Tunisian and Egyptian uprisings. Go play.
Derek Watkins put together this video visualizing the expansion of the United States from 1700 to 1900 through the establishment of post offices.
Visualizing ten years of violence against journalists in Afghanistan
Internews and Nai, an Afghan media advocacy organization, have collected hundreds of reports of threats, intimidation, and violence faced by journalists in Afghanistan. We recently announced a new site, data.nai.org.af, which features 10 years of these reports. While Nai’s data previously resided in spreadsheets, the new site allows the public to access hundreds of reports through visualizations and to download it directly. With this site we’re raising the profile of media freedom in a country often characterized as among the most dangerous in the world for journalists.
Take, for example, the case of Omaid Khpalwak, a reporter with Pajhwok Afghan News who died recently in an attack on Tarin Kot, capital of Uruzgan.
Freelance journalists are among the top five groups experiencing violence. The others are formal news organizations.
For data wranglers, Internews and Nai are releasing the data in .csv and .geoJSON formats.
You can explore the infographic and export the data here.
“@keithurbahn … was not first to speculate that the [Obama] address was related to Bin-Laden, nor did he have a particularly influential presence on Twitter, with a following of 1,016 and a casual digital portrayal. But the right network effects came into play, and enabled his post to generate enough trust amongst his followers, their followers, and so on.”
The bin Laden news: How a single tweet spread like wildfire. (Click through for full visualization from SocialFlow Company Blog)