‘Without any mental deliberation, picture the average female porn star. Just let her spring into your mind’s eye looking however she looks. Can you see her?’
I’d bumped into a friend who I’d not seen in a while and this was the first question I asked him. He didn’t realise at the time that I’d be in self-imposed smutty exile for an untold number of weeks, working on the largest study of porn stars ever undertaken, and now I was out and eager to spread the news.
‘Erm, yeah, I suppose,’ he said.
‘What does she look like?’ I asked, struggling to hide my smile.
When he replied by saying ‘a blonde with big boobs’, I must admit I relished the opportunity to lean in, let the grin spread across my tired face, and say ‘That’s what everyone says. And in fact, it’s wrong’.
‘Oh,’ he said, after I explained how I knew what the average porn star actually looks like, as well what her name probably is, how many films she’s most likely done and the probability of her having a tattoo or body piercing.
‘So you’ve spent all this time watching hundreds of porn movies?’
‘No,’ I said. ‘I’ve spent all this time analysing the demographic profiles and filmographies of ten thousand adult performers. There is a difference.’
‘I see’, he then said. ‘And how, dare I ask, does one go about doing that?’
There’s data porn and there’s porn data. Combining the two is Jon Millward, a self-described “Ideas Detective”.
Millward spent six months going over a ten thousand person porn star database to determine “what the average performer looks like, what they do on film, and how their role has evolved over the last forty years.”
The result is both a longread analysis and multiple data visualizations of things you never know you’d be interested to know.
Jon Millward, Deep Inside: A Study of 10,000 Porn Stars and Their Careers.
Somewhat related: Sex Diseases Cost $16 Billion a Year to Treat, CDC Says
Georgia congressman Paul Broun claimed after Tuesday’s State of the Union address that “There are more people killed with baseball bats and hammers than are killed with guns.” Explainer readers may remember Broun as the congressman who believes the Earth is 9,000 years old. What about his hammer and baseball bat claim?
He’s wrong again, but he’s getting warmer. According to FBI data, 8,583 people were murdered with firearms in 2011. Only 496 people were killed by blunt objects, a category that includes not just hammers and baseball bats but crowbars, rocks, paving stones, statuettes, and electric guitars. Broun was off by a factor of at least 17 this time, a significant improvement on his estimate of the age of the Earth. The blue planet is 4.54 billion years old, or more than 500,000 times older than Broun believes it to be.
FJP: …but he’s getting warmer.
Words and phrases are fundamental building blocks of language and culture, much as genes and cells are to the biology of life. And words are how we express ideas, so tracing their origin, development and spread is not merely an academic pursuit but a window into a society’s intellectual evolution.
In the report, Twitter said that, worldwide, it received 1,858 requests from governments for information about users in 2012, as well as 6,646 reports of copyright violations, and 48 demands from governments that content they deem illegal be removed.
I say that news organizations should become advocates for open information, demanding that government not only make more of it available but also put it in standard formats so it can be searched, visualized, analyzed, and distributed. What the value of that information is to society is not up to the gatekeepers — officials or journalists — to decide. It is up to the public.
Jeff Jarvis, BuzzMachine. Public is public… except in journalism?
While the above quote may stand on its own, a little context: not everyone liked the map of gun permit owners that was published in the aftermath of the Sandy Hook shooting. Jarvis believes that the decision of whether or not the map is morally sound belongs to the public — not to journalists.
Other media thinkers have said otherwise. The Times’ David Carr argued yesterday that the map, which showed the addresses of gun permit owners in New York’s Westechester and Rockland counties, isn’t journalism.
Well, is it?
While Twitter’s Turks will help bring much-needed context to the platform, they’re not journalists who verify whether something is true. As we’ve seen with the shootings in Newtown, Connecticut and Superstorm Sandy, Twitter rumors ran rampant. Some rumors turned out to be true, but many were inaccurate or even malicious. Some were important, others were trivial. At Breaking News, we rely on experienced journalists (that’s one of them, Stephanie Clary, above) to verify real-time reports and prioritize their importance. We also add context, associating reports with ongoing stories, topics and locations. But accuracy and importance — along with speed — are the essence of breaking news for any news organization.
The Breaking News team to Twitter: Your Mechanical Turk team can’t compete with our actual journalists. (via shortformblog)
FJP: Some Background — The Twitter Engineering blog posted yesterday about how it uses real people alongside its search algorithms to determine the “meaning” of trending terms. It does this with both in-house evaluators and Amazon’s Mechanical Turk, a crowdsourced marketplace for accomplishing (relatively) small tasks.
The goals is to contextualize and understand, for example, that something like #BindersFullOfWomen is related to politics.
Here’s what Twitter has to say about what happens when topics begin to trend:
As soon as we discover a new popular search query, we send it to our human evaluators, who are asked a variety of questions about the query… For example: as soon as we notice “Big Bird” spiking, we may ask judges on Mechanical Turk to categorize the query, or provide other information (e.g., whether there are likely to be interesting pictures of the query, or whether the query is about a person or an event) that helps us serve relevant Tweets and ads.
We need, in short, to pay attention to the materiality of algorithmic processes. By that, I do not simply mean the materiality of the algorithmic processing (the circuits, server farms, internet cables, super-computers, and so on) but to the materiality of the procedural inputs. To the stuff that the algorithm mashes up, rearranges, and spits out.
CW Anderson, Culture Daily. The Materiality of Algorithms.
In what reads like a starting point for more posts on the subject, CUNY Prof Chris Anderson discusses what documents journalists may want to design algorithms for, and just how hard that task will be.
Algorithms doing magic inside massive data sets and search engines, while not mathematically simple, are generally easy to conceptualize — algorithms and their data are sitting in the computer, the algorithm sifts through the excel sheet in the background and bam! you have something.
But if you’re working with poorly organized documents, it’s difficult to simply plug them in.
Chris writes that the work required to include any document in a set will shape the algorithm that makes sense of the whole bunch. This will be a problem for journalists who want to examine any documents made without much forethought, which is to say: government documents, phone records from different companies and countries, eye witness reports, police sketches, mugshots, bank statements, tax forms, and hundreds of other things worth investigating.
The recovered text [from these documents] is a mess, because these documents are just about the worse possible case for OCR [optical character recognition]: many of these documents are forms with a complex layout, and the pages have been photocopied multiple times, redacted, scribbled on, stamped and smudged. But large blocks of text come through pretty well, and this command extracts what text there is into one file per page.
To read the rest of Stray’s account, see his Overview Project.
And to see more with Chris Anderson, see our recent video interviews with him.