communication. community. cognition.
I Kant understands teh Intarwebs.
And it has nothing to do with the ridiculous spelling, whether it’s the LOLcats feigned ignorance, or the intentional crop-and-drop of letters. (I’m looking at you, Flickr and Tumblr.)
The mystery is in the origin of our online etiquette and morality.
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I don’t mean to pick on Good Morning America because it’s bad. It’s not. In fact, it is the only TV news I regularly subject myself to anymore. They probably do as well or better than any of the other networks.
Which is sad, because what passes for news these days is not news, it’s wrong.
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Vanity… all is vanity.
I think Solomon had it right.
Yet in an age of Information Flood, part of our task is to help relevant and useful information be found.
In the process, we’re just going to have to sacrifice quality.
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Three-and-a-half years ago, I wrote a spoof about how analysis of mood and syntax on Twitter could be used to predict a woman’s likely moment of ovulation.
A year-and-a-half ago, I wrote a piece about how Google was assembling a significant-enough chunk of content creation and distribution, it would have a prediction engine that could intelligently mine for patterns, and maybe even pick stocks. (All that Google lacked was a micro-blog style service, like Twitter.)
And now?
An analysis of almost 10 million tweets from 2008 shows how they can be used to predict stock market movements up to 6 days in advance.
Give it a read. Actually, give them all a read.
Most internet users don’t remember a time before there was a Google. (Those who do likely were grimacing over my failure to capitalize Internet.) For those who made surfing a dry activity since 2000, there has always been an Algorithm in the background, providing order to the vast online Universe.
What Google did was promote the idea that an unseen formula could improve your search results. Human-inspired and seeded indexes could not scale to cover the exponentially-growing feed of data – and we needed a Secret Sauce to sort it all out.
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I don’t like talking about current events much, because they have a tendency to soon be not-so-current. But one in particular may signal the tipping point of a trend that is of extreme relevance to the way you and I find useful information.
The rumor is that Google is developing a true Facebook competitor called “Google Me.” I’m not interested in the details of whether they are, but rather the facts behind why Google needs to.
There are always the concerns when a business gets away from its core, and Google has had its share of outright bumbles. Buzz and Wave may not be great, but they aren’t horrible either. And when you’re the size of Google, you don’t pretend to live in just one box. In fact, you could say the acquisition of Youtube was brilliant, as Youtube is now the world’s number two search engine (behind the almighty G itself.) Youtube might never turn a profit, but there’s no telling how valuable the data under the surface might be.
Which brings us to the reason Google ought to be firing up a major competitor to Facebook: because Facebook may yet provide the greatest threat to Google’s core search business. [Read more...]
If you stare at the lines in the road, you’ll never see where you’re going.
While the Devil might be in the details, if you want to know where he’ll be you need to look for the pattern. Pattern-recognition is one of the trickiest pieces of programming, partially because we know very little about how our brains work, and partially because humans make it look so damned easy. Our brains are designed to spot and record patterns.
Sure, it takes a long time. Evenutally, enough memories gel to enable us to look back and assign confidence of some correlation (if not causation.)
Red sky at night, sailor’s delight. Red sky at morning, sailor take warning.
That won’t hold up against the very best prediction engines we have, but it got us down that path. You go back and examine what happened before an event to determine what contributed.
Meanwhile, 200,000 people died at the end of 2005 because no one made the correlation that a big underwater earthquake might pose a problem. There was no warning for the tourists who were trapped by the wall of water. There was a warning for the Indonesian natives who knew that a sudden and unexpected ebb tide was a sign of a huge wave coming in. Many of the animals knew it, too.
It always seems far simpler when you know what the trigger is, instead of drowning yourself in a myriad of probably inconsequential details.
This post is more straightforward than I wanted it to be. It was originally envisioned as a short story describing the greatest effort in the fictional history of programming. Only I am not so sure it is fictional. It is too possible to not be probably, and world domination is potentially at stake.
I rush this essay into publication because of a fractured discussion with Steve Rubel, who tracks all things technology. Google has announced it is shutting down several of its free webservices, and Rubel mentioned in passing that Google Reader might not survive the next round without showing some value.
Reader is an RSS feed reading application. You ‘subscribe’ to blogs and content that you like online, and Reader ‘delivers’ it to you. Instead of clicking links and folders and bookmarks, the Web you like comes to you in one quick and tidy place. You can also subscribe to feeds of news searches, or mix and match your own sources.
Google Reader offers a couple of very useful features. One, all the feeds I subscribe to are searchable using the Google indexing and algorithm. I don’t have to ‘file’ things in my Reader, I can always find them later. If I choose, I can add whatever tags and descriptors I deem relevant. Second, I can share links with people I know. Real-life friends, business acquaintances, or those I network with online. I actually get ‘feeds’ of what my network of people found interesting, and we can add notes to each other pointing out key facts or summaries.
What makes this interesting is Google’s role throughout. In the course of the content, Google plays several key roles. Not a monopoly, but it is a player in:
No one else is a significant-enough player in all these aspects of the Information Age to track what is said to whom, and when it happens.
If you’re Google, you have Willy Wonka’s Golden Ticket: the map to the influencers. There’s a huge debate raging among the marketers and the public relations people and the politicos over just who has influence, and how you locate them.
Finding Influencers is important, because it allows you to target your message or your plea to only those people that really matter for a given function or moment. Those Influencers can change over time or given a different objective, but locating them is the key.
From the instant someone creates a video or a blog post, Google knows what is in it. (Again, there are other services, but Google gets enough of the video and blog business to make this scale.) Google also knows:
…and the cycle continues. From Soup to Nuts, Google can know which people start the online tremors that lead to popularity of content. ‘Viral’ is no longer a marketing mystery – Google has the data to find the epidemiology.
Willy Wonka’s Golden Ticket wasn’t the prize itself – it was the step you had to clear to get to the prize.
Sure, Google could sell some of those results. It could offer up premium information to advertisers, or even offer direct targeted ads at the highest of most high Influencers. We’re not talking about the Pete Cashmores or Steve Rubels of the world – we want the people who are more likely to seed them with inspiration and information.
But even that isn’t the prize. Stay with me here.
Get several million people on Blogger, a large contingent of content producers. Get a couple of million more on Google Reader, and then sit back for about five years while they share data like no one’s business.
Except it is your business. You need to understand who the Nodes are, and how much time elapses between certain events. You need to learn how to look beyond the tiny pieces of data as individual bits, and instead look at the whole. Big picture, a bunch of water droplets becomes a cloud. And under certain atmospheric conditions, that cloud looks red.
Google isn’t going to drop Reader, because it needs us to keep feeding the data beast. It will take a good five years of collection (and maybe a couple of more concentrating on the data visualization to make it feasible, but isn’t that why Google hired all those engineers and algorithm people?)
Once you know what a ripple looks like, and the content of that ripple, you can track it. And you start to see the others. And eventually, you start to identify the ripples that preceded a discrete event instead of the ones that followed.
Google is building the world’s largest prediction engine. It’s now in a learning phase, and an early one at that. It’s building a new Vocabulary of Influence, not to sell us products but instead to tell the future. All you need is a series of similar events that you can compare, and look for correlating ripples that came before. Certain punctuated events would have no meaning, like outcomes of Super Bowls. But something like, say, a quarterly stock report, would be easy to parse.
It would be regular enough (and have a large enough data mine of its own) that you could put the most powerful computers to work just looking for the pattern. And as the owner of the ONLY data set that traces complete ripples of influence, there is no break in the chain to cloud the data.
Maybe the predictions will come with just a few hours notice, like a tsunami warning system. Maybe it will evolve into a longer-range forecasting tool for economics or finance. What could Larry and Sergey do with the Ginormous Google Gigawatt Crystal Ball? Other than promise us they Won’t Be Evil?
The truth is right there in your Google Reader, and the Devil is in your details. And that is why the High Holy Priests of Mountain View will never bring Reader to the sacrificial altar.
