• by Gordon Gould , September 10, 2008

When I first logged onto the Net 18 years ago, like everyone else I was mesmerized. I was excited just to be online. Since then, our perception of the Internet's value has changed drastically, and I'm only beginning to realize how much.

Let's break it down: Web 1.0 was about getting online. Web 2.0 was a quantum leap forward that let people share. It sounds simple, but it was a profound evolutionary jump that brought with it a host of advantages...and not a few problems. The forward-thinkers have been bandying about the term "Web 3.0" lately, but what does it really mean?

But before we go forward, let's return to the beginning.

Through Web 1.0, we learned that a truly open form of communication has limitless possibilities. Shifting behaviors from a top-down, one-to-many model (think of television, radio and print) to a community paradigm was really an afterthought. Chat rooms - where people discussed everything and nothing - were the precursor to the social Web.

Which brings us to Web 2.0, a two-way conversation between consumers and brands, between members of a community, between bloggers and just about anybody. Now the conversation has a real purpose. Social media - blogs and microblogs, etc. - and social networking show us that this new Internet iteration is no longer about merely getting online but about what to do once you're there.

I define Web 2.0 as sharing -information, personality, personal and professional contacts. As people become more comfortable with 2.0, we've seen an explosion of user-generated content (UGC), which, ironically, causes a major problem: information overload. This begs the question: "Is there such a thing as too much sharing?"

Wait for it...yes.

Searching online content today can be like wading through an information quagmire, and, as a result, the Internet is in need of another evolutionary leap. Filtering.

Remember how "sharing" sounded simple? Filtering is anything but simple, and more to the point, it is essential.

Web 3.0 is about creating personal and reliable filters that will help users sift through UGC to find credible sources and those they trust. Imagine you're attending a lecture at which Socrates will share his most profound insights, but you walk into the lecture hall to find 500 people dressed in togas all yammering at once. Which one is Socrates? Which people are speaking gibberish and which are dispensing pearls of wisdom? Now bring it back to the present and imagine how we will evaluate what content online and, as importantly, who is credible.

When I go looking for a good read, I find myself going right to the blurbs. If reputable people and publications recommend the book, I buy it. We need to give UGC credibility and authenticity in the same way we give "real-life" people power over our choices. Not only that, but we'll also be able to transfer someone's credibility from one site to another.

In fact, people gain credibility in three ways: large reach (do you have a large social network?), "Q" factor (do people find you interesting?), and generating content (are you uploading content that I agree with and ostensibly respect?).

Take Twitter. I follow many people because I'm interested in hearing what they have to say. I then look at who those people follow and determine, based on the above criteria, if they are someone I should know more about. Some people have thousands of followers because they have proven that following them is worthwhile.

Many of these Twitterers have taken their credibility from other areas - offline, other social sites, and blogs - and define themselves as authentic sources of reliable information. But these are early adopters. Soon companies, marketers, and consumers will have to figure out how to filter all these sources to make messages relevant and credible to individuals. "How?" remains the question.

Algorithms, expediency, prediction, reach and influence.

Algorithms have made the Web indispensable. They speed up our research and help us find what we're looking for. As vital as they are now, in the social world of 3.0 algorithms will be even more crucial in acting as a filter serving as the backbone to the other methods.

What we're talking about when we refer to expediency in social media is finding stuff first - whether it's the next big consumer item or a hot news scoop. Web users who have their finger on the pulse of emerging trends will convert their expert knowledge into influence because they get the information first. Sites like TechCrunch and Mashable are fine examples, transferring speedy information into resources that are valuable to their hungry participants.

Prediction is just what it sounds like: Internet users who successfully predict taste. They build a following because what they have to say is entertaining, intriguing, and just far enough ahead of the curve to be considered trendsetting.

Reach describes the size of one's following and influence describes how well your network listens to you. Taking an influencer's credibility to other social networks/sites (credibility portability) will directly relate to the amount of reach the person has. Similarly, the larger one's reach, the greater the influence.

The social Web's soapbox hasn't gotten bigger, but the number of people that surround it has. We need to find those Web 3.0 filters that are going to be influential and important to us if we're going to, as in any new discovery, sift the wheat from the chaff.