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Check out my new piece on ReadWriteWeb about the latest goings on at Digg. Link here…

Fascinating article in the NYT today (I am again quoting NYT…It seems they have really gotten their act together of late in the high-tech/network world space). The article talks about the theory of “Cumulative Advantage” or the “rich get richer” effect. In summary the theory suggests that our preferences/decisions are very much effected by what other people are doing. So if a technology or a singer or a movie is liked by our peers we are more likely to try it and like it. We provided another example of this phenomenon (without naming the theory) in a prior post related to behavior of users at Digg where we observed that a fake article got a number of Diggs just because a user paid of a few Diggs to get initial momentum.

Conventional marketing wisdom holds that predicting success in cultural markets is mostly a matter of anticipating the preferences of the millions of individual people who participate in them. From this common-sense observation, it follows that if the experts could only figure out what it was about, say, the music, songwriting and packaging of Norah Jones that appealed to so many fans, they ought to be able to replicate it at will. And indeed that’s pretty much what they try to do. That they fail so frequently implies either that they aren’t studying their own successes carefully enough or that they are not paying sufficiently close attention to the changing preferences of their audience.

The common-sense view, however, makes a big assumption: that when people make decisions about what they like, they do so independently of one another. But people almost never make decisions independently — in part because the world abounds with so many choices that we have little hope of ever finding what we want on our own; in part because we are never really sure what we want anyway; and in part because what we often want is not so much to experience the “best” of everything as it is to experience the same things as other people and thereby also experience the benefits of sharing.

The authors set out to test out the theory with an interesting experiment:

Because it’s not possible in the real world to test theories about events that never happened, most of what we know about cumulative advantage has been worked out using mathematical models and computer simulations — an approach that is often criticized for glossing over the richness of real human behavior. Fortunately, the explosive growth of the Internet has made it possible to study human activity in a controlled manner for thousands or even millions of people at the same time. Recently, my collaborators, Matthew Salganik and Peter Dodds, and I conducted just such a Web-based experiment. In our study, published last year in Science, more than 14,000 participants registered at our Web site, Music Lab (www.musiclab.columbia.edu), and were asked to listen to, rate and, if they chose, download songs by bands they had never heard of. Some of the participants saw only the names of the songs and bands, while others also saw how many times the songs had been downloaded by previous participants. This second group — in what we called the “social influence” condition — was further split into eight parallel “worlds” such that participants could see the prior downloads of people only in their own world. We didn’t manipulate any of these rankings — all the artists in all the worlds started out identically, with zero downloads — but because the different worlds were kept separate, they subsequently evolved independently of one another.

This setup let us test the possibility of prediction in two very direct ways. First, if people know what they like regardless of what they think other people like, the most successful songs should draw about the same amount of the total market share in both the independent and social-influence conditions — that is, hits shouldn’t be any bigger just because the people downloading them know what other people downloaded. And second, the very same songs — the “best” ones — should become hits in all social-influence worlds.

What we found, however, was exactly the opposite. In all the social-influence worlds, the most popular songs were much more popular (and the least popular songs were less popular) than in the independent condition. At the same time, however, the particular songs that became hits were different in different worlds, just as cumulative-advantage theory would predict. Introducing social influence into human decision making, in other words, didn’t just make the hits bigger; it also made them more unpredictable.

Where does this leave us with the rational choice and perfect market theory? Do you think people are more rational when it comes to money? What about making investments? How should VCs or any investor for that matter, evaluate a new consumer technology or a mass market product? This is powerful stuff.

Fascinating piece on the Wired web site, related to how the editors put together a nonsensical web site, and got it on the front page of Digg by paying for diggs at User/Submitter (check out our review here) site:

Ten hours after hiring U/S, I had 40 diggs. The vast majority of them had also dugg the Photoshop tutorial or the $35 offer. This was the moment when I reached a tipping point, and I began to get a lot of organic diggs and comments. The crowd on Digg is drawn to what’s popular, and many of them second-guessed themselves when they checked out my blog and saw how crappy it was. Quomen commented, “None of those photographs really appeal to me. Am I defective? or just a loner.”Despite their doubts, Diggers kept digging my blog. There’s a perverse incentive here: Diggers who vote early on stories that become wildly popular become more “reputable” in the Digg system. If you’re trying to move up the Digg ranks, it’s in your best interest to vote on anything that looks like it’s gaining popularity. And my blog, with its flurry of paid votes, fit the pattern.

Interesting crowd dynamics at the Digg and the incentive structure does not help either…I have actually seen people comment they are not sure what a particular topic means but still Digg it. In this case more than 1/2 the Diggs were unpaid…That is just unbelievable. I guess the momentum trading theory is alive and kicking.

“We find it interesting that Digg still allows anybody to view any user’s diggs,” U/S told me in an e-mail. “By way of this ‘feature,’ User/Submitter is able to verify that our users actually digg the stories they’re given. Without this feature, Digg users are given complete digging privacy, and User/Submitter cannot exist.”

This is another perverse incentive…but this is driven by Digg’s drive to build a community. To fix this one, they will need to change the business model…All in all great job by the editors for creating and publishing this interesting experiment.

Things are just going crazy for OpenID…Digg just announced that it is planning to support OpenID. While its not that big a deal in raw numbers (see our coverage of AOL announcement, which is far bigger in terms of sheer numbers), it is a pretty big deal in terms of buzz and the demographic group it effects and therefore could have a pretty significant effect of the adoption of OpenID.

It looks like the OpenID solution is snowballing…I don’t want to sound a pessimistic note but I just hope the community figures out the solution to the phishing issues (see our analysis here) before too late.

See more coverage GigaOM, TechCrunch, RWW

Yahoo! has launched a new site for having their users vote on the new features. Yahoo! blog Yodel Anecdotal describes the feature as below:

When you find something broken on the Web, product folks at small web sites are usually easy to connect with. But visitors to sites with significant traffic usually have a tougher time lobbing input directly to site development teams about the good, the bad, and the screwed up. That’s changing for Yahoo! — we’ve brewed up a swanky new community-based recipe for collecting feedback that’s making its way across a number of our sites. It started with Yahoo! Autos and has proliferated across 14 other properties.

We call it a Suggestion Board — you can browse suggestions from other site visitors or post your own. Digg-style voting means we can quickly discover what’s most important to users. In addition to reading feedback from other users, you’ll find responses from Yahoo! employees about the issues. Product teams regularly read and take action on your feedback. Though we aren’t always going to immediately act on it, it’s incredibly helpful to us in making the best sites we can… and we’ve even been known to reward great suggestions with some Yahoo! schwag.

Check out the Suggestion Boards that are now live: Answers, Autos, Autos Custom, My Yahoo!, Pipes, Real Estate, Site Explorer, Travel, TV, Upcoming.org, Yahoo! Developer Network, and Yahoo! Developer Network Gallery.

There is a lot of Buzz around the blogosphere and Digg about the similarities between the Yahoo!’s and Digg’s model for voting. But beyond that I think this is a very clever way for Yahoo! to take a pulse of the users. I tend to think that Yahoo! Suggestion Board might be a better application of social voting then Digg like social bookmarking where voting tends to go in herds. One way Yahoo! can improve the product is by limiting the number of votes each user can make, thereby forcing them to be judicious. Another way to empower the community could be to commit to implementing 10% of the top user suggestions in the course of next release. (I guess I should post the suggestion at the suggestion board, suggestion board:-)). In fact, if you are a product manager at a big company, this kind of application could prove valuable in setting short term and long term product direction…Anybody working on that???