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Original author: 
Cory Doctorow

Google's rolled out an "Inactive Account Manager" -- a dead-man's switch for your Google accounts. If you set it, Google will watch your account for protracted inactivity. After a set period, you can tell it to either squawk ("Email Amnesty International and tell them I'm in jail," or "Email my kids and tell them I'm dead and give them instructions for probating my estate") and/or delete all your accounts. This has a lot of use-cases, from preventing your secrets from being tortured out of you (before you go to a protest, you could set your dead-man's switch to a couple hours -- if you end up in jail and out of contact, all your stuff would be deleted before you were even processed by the local law) to easing the transition of your digital "estate."

No one wants to think about their own death, but not thinking about it has a zero percent chance of preventing it. The Inactive Account Manager (great euphemism) can send your data from many Google services to your digital heirs, alert your contacts, delete the accounts, or do all or none of the above. It affects Blogger, Contacts/Circles (in Google+) Drive, Gmail, Google+ profiles, Pages and Streams, Picasa albums, Google Voice, and YouTube.

It also serves as a useful self-destruct button. Don’t want anyone watching your stupid YouTube videos after you’ve long forgotten that you had an account? Don’t want your kids to find your password notebook years after you’re gone and read your dirty chat sessions with their dad? You can have your account auto-destruct after trying to reach you using other e-mail addresses and by text message. You know, in case you just get tired of Gmail and wander off somewhere else.

Google Introduces Dead Man’s Switch For Your Accounts     

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Original author: 
Cory Doctorow

In Wired, Steven Levy has a long profile of the fascinating field of algorithmic news-story generation. Levy focuses on Narrative Science, and its competitor Automated Insights, and discusses how the companies can turn "data rich" streams into credible news-stories whose style can be presented as anything from sarcastic blogger to dry market analyst. Narrative Science's cofounder, Kristian Hammond, claims that 90 percent of all news will soon be algorithmically generated, but that this won't be due to computers stealing journalists' jobs -- rather, it will be because automation will enable the creation of whole classes of news stories that don't exist today, such as detailed, breezy accounts of every little league game in the country.

Narrative Science’s writing engine requires several steps. First, it must amass high-quality data. That’s why finance and sports are such natural subjects: Both involve the fluctuations of numbers—earnings per share, stock swings, ERAs, RBI. And stats geeks are always creating new data that can enrich a story. Baseball fans, for instance, have created models that calculate the odds of a team’s victory in every situation as the game progresses. So if something happens during one at-bat that suddenly changes the odds of victory from say, 40 percent to 60 percent, the algorithm can be programmed to highlight that pivotal play as the most dramatic moment of the game thus far. Then the algorithms must fit that data into some broader understanding of the subject matter. (For instance, they must know that the team with the highest number of “runs” is declared the winner of a baseball game.) So Narrative Science’s engineers program a set of rules that govern each subject, be it corporate earnings or a sporting event. But how to turn that analysis into prose? The company has hired a team of “meta-writers,” trained journalists who have built a set of templates. They work with the engineers to coach the computers to identify various “angles” from the data. Who won the game? Was it a come-from-behind victory or a blowout? Did one player have a fantastic day at the plate? The algorithm considers context and information from other databases as well: Did a losing streak end?

Then comes the structure. Most news stories, particularly about subjects like sports or finance, hew to a pretty predictable formula, and so it’s a relatively simple matter for the meta-writers to create a framework for the articles. To construct sentences, the algorithms use vocabulary compiled by the meta-writers. (For baseball, the meta-writers seem to have relied heavily on famed early-20th-century sports columnist Ring Lardner. People are always whacking home runs, swiping bags, tallying runs, and stepping up to the dish.) The company calls its finished product “the narrative.”

Both companies claim that they'll be able to make sense of less-quantifiable subjects in the future, and will be able to generate stories about them, too.

Can an Algorithm Write a Better News Story Than a Human Reporter?

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Michael B. Morgan, CEO of Morgan & Claypool Publishers, writes:

In 2009, we invited Aaron Swartz to contribute a short work to our series on Web Engineering (now The Semantic Web: Theory and Technology). He produced a draft of about 40 pages -- a "first version" to be extended later -- which unfortunately never happened.

After his death in January, we decided (with his family's blessing) that it would be a good idea to publish this work so people could read his ideas about programming the Web, his ambivalence about different aspects of Semantic Web technology, his thoughts on Openness, and more.

As a tribute to Aaron, we have posted his work on our site as a free PDF download. It is licensed under a Creative Commons (CC-BY-SA-NC) license. The work stands as originally written, with only a few typographical errors corrected to improve readability.

Aaron Swartz's A Programmable Web: An Unfinished Work

Aaron Swartz’s
A Programmable Web:
An Unfinished Work
(PDF)

(Thanks, Michael!)

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Oona Räisänen has written a thorough and engrossing article about the noises emitted by dial-up modems while they connect and handshake, and the accompanying graphic (ZOMG HUGE) is nothing short of spectacular. It would make a great full-size poster -- maybe a framed art-print.

Now the modems must address the problem of echo suppression. When humans talk, only one of them is usually talking while the other one listens. The telephone network exploits this fact and temporarily silences the return channel to suppress any confusing echoes of the talker's own voice.

Modems don't like this at all, as they can very well talk at the same time (it's called full-duplex). The answering modem now puts on a special answer tone that will disable any echo suppression circuits on the line. The tone also has periodic "snaps" (180° phase transitions) that aim to disable yet another type of circuit called echo canceller.

Now the modems will list their supported modulation modes and try to find one that both know. They also probe the line with test tones to see how it responds to tones of different frequencies, and how much it attenuates the signal. They exchange their test results and decide a speed that is suitable for the line.

After this, the modems will go to scrambled data. They put their data through a special scrambling formula before transmission to make its power distribution more even and to make sure there are no patterns that are suboptimal for transfer. They listen to each other sending a series of binary 1's and adjust their equalizers to optimally shape the incoming signal.

The sound of the dialup, pictured

(via JWZ)

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Upworthy, a startup that helps promote material via "viral" distribution, has posted a short slideshow with some interesting (and depressing -- it all comes down to horrible Facebook) insights into how things become popular online.

How To Make That One Thing Go Viral

(via O'Reilly Radar)

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In "Credibility ranking of tweets during high impact events," a paper published in the ACM's Proceedings of the 1st Workshop on Privacy and Security in Online Social Media , two Indraprastha Institute of Information Technology researchers describe the outcome of a machine-learning experiment that was asked to discover factors correlated with reliability in tweets during disasters and emergencies:

The number of unique characters present in tweet was positively correlated to credibility, this may be due to the fact
that tweets with hashtags, @mentions and URLs contain
more unique characters. Such tweets are also more informative and linked, and hence credible. Presence of swear words
in tweets indicates that it contains the opinion / reaction of
the user and would have less chances of providing informa-
tion about the event. Tweets that contain information or
are reporting facts about the event, are impersonal in nature, as a result we get a negative correlation of presence of
pronouns in credible tweets. Low number of happy emoticons [:-), :)] and high number of sad emoticons [:-(, :(] act
as strong predictors of credibility. Some of the other important features (p-value < 0.01) were inclusion of a URL in
the tweet, number of followers of the user who tweeted and
presence of negative emotion words. Inclusion of URL in a
tweet showed a strong positive correlation with credibility,
as most URLs refer to pictures, videos, resources related to
the event or news articles about the event.

Of course, this is all non-adversarial: no one is trying to trick a filter into mis-assessing a false account as a true one. It's easy to imagine an adversarial tweet-generator that suggests rewrites to deliberately misleading tweets to make them more credible to a filter designed on these lines. This is actually the substance of one of the cleverest science fiction subplots I've read: in Peter Watt's Behemoth, in which a self-modifying computer virus randomly hits on the strategy of impersonating communications from patient zero in a world-killing pandemic, because all the filters allow these through. It's a premise that's never stopped haunting me: the co-evolution of a human virus and a computer virus.

Credibility Ranking of Tweets during High Impact Events [PDF]

(via /.)

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Biella Coleman is a geek anthropologist, in both senses of the epithet: an anthropologist who studies geeks, and a geek who is an anthropologist. Though she's best known today for her excellent and insightful work on the mechanism and structure underpinning Anonymous and /b/, Coleman is also an expert on the organization, structure, philosophy and struggles of the free software/open source movements. I met Biella while she was doing fieldwork as an intern at the Electronic Frontier Foundation. She's also had deep experience with the Debian project and many other hacker/FLOSS subcultures.

Coleman's has published her dissertation, edited and streamlined, under the title of Coding Freedom: The Ethics and Aesthetics of Hacking, which comes out today from Princeton University Press (Quinn Norton, also well known for her Wired reporting on Anonymous and Occupy, had a hand in the editing). Coding Freedom walks the fine line between popular accessibility and scholarly rigor, and does a very good job of expressing complex ideas without (too much) academic jargon.

Coding Freedom is insightful and fascinating, a superbly observed picture of the motives, divisions and history of the free software and software freedom world. As someone embedded in both those worlds, I found myself surprised by connections I'd never made on my own, but which seemed perfectly right and obvious in hindsight. Coleman's work pulls together a million IRC conversations and mailing list threads and wikiwars and gets to their foundations, the deep discussion evolving through the world of free/open source software.

Coding Freedom: The Ethics and Aesthetics of Hacking

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Sam from MIT sez, "This 2-day conference at MIT brings together 50 leading thinkers about innovation in the media and marketing industries. Issues tackled include the importance of listening to their audiences and putting yourself in their shoes; the politics and ethics of curation in a spreadable media world; the move from "participatory culture" to "political participation," curing "the shiny new object syndrome" of putting the hype of new platforms over storytelling strategy, and rethinking copyright for today's world. The conference also includes particular looks into the futures of video gaming, the futures of public media, and the futures of storytelling in sports. Speakers include T Bone Burnett, Henry Jenkins, Maria Popova, Grant McCracken, Jason Falls, Valve Software's Yanis Varoufakis, PBS FRONTLINE's Andrew Golis, Google Creative Lab Director Ben Malbon, Xbox co-founder Ed Fries, AT&T AdWorks Lab Director David Polinchock, the creators of 30 Mosques in 30 Days, and USC Annenberg Inno vation Lab Director Jon Taplin. Also, there's a pre-conference event Thursday evening, Nov. 8, on 'New Media in West Africa,' moderated by mobile entertainment founder Ralph Simon and featuring the Harvard Berkman Center's Colin Maclay, artist Derrick Ashong, and iROKOtv's Fadzi Makanda."

Futures of Entertainment 6 | November 9-10, 2012 MIT, Cambridge MA

(Thanks, Sam!)

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On CNN, Doug Gross has a good account of Kevin Smith's SXSW presentation on how he became a podcaster and weaned himself off the "heroin" of movie studio money, going direct to his fans instead for advertising, merch sales and sold-out houses when he toured. This being CNN, they've got a lot of [expletive] marks where Smith is saying "fuck" in his charmingly innocent way.

Smith said he decided to take advantage of his access to celebrities and gift of gab to launch a new project. And he deployed a technique he said has always served him well: do what you love and what you're good at, then figure out how to make money doing it.

And that led to "SModcast," a weekly podcast that he and friend/co-producer Scott Mosier launched in 2007 and do to this day.

It was free. But as its online audience grew, the opportunities to make money arose.

"People would tweet left and right: 'You put out so many free podcasts; how can I pay it back?' " said Smith, who has more than 2 million followers on Twitter. "I was like, 'Go buy a T-shirt' and they were like, 'Cool.' "
,p>
Then came paid advertising. (The first sponsor notoriously being adult product Fleshlight). Then a paid version of the podcast, "SModcost," which contains bonus features but no ads.

Filmmaker Kevin Smith: Podcasting saved my career

(Image: Kevin Smith in Vancouver, a Creative Commons Attribution (2.0) image from shaynekaye's photostream)

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On Ars Technica, Tom Connor does a great job producing a taxonomy and history of rage-faces, showing how they evolved from a set of proscribed, orthodox uses on 4chan to a wider set of uses and meanings in several online communities.

Rage faces slowly migrated from 4chan into other communities. There, they gained popularity and expanded their numbers as artists introduced new faces, and particularly humorous comics went viral in their communities. Though the faces were no longer exclusive to any single forum, they stayed true to the originals in style.

More people got involved, the cartoons mutated and evolved, and like any successful species, they adapted to fit into a wide variety of habitats. "You can trace back the origins to 4chan so you can say [the faces are 4chan's] baby, but it's evolved on such a wide scale that it's gone beyond anyone's single ownership," Swanson said. "Mostly the original faces are from 4chan, but a lot of the newer faces have come out of F7U12, or other places like FunnyJunk."

Fffuuuuuuuu: The Internet anthropologist's field guide to "rage faces"

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