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Docstoc founder Jason Nazar sends in a humorous screen capture from Digg. Refresh this story titled “Living With A Drug Dealer As A College Roommate” enough times and you’ll see a house advertisement for upcoming Digg meetups. That ad, matched with the story, begs the question, which one is the drug dealer?

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Reports are bubbling up that Digg has permanently banned over 80 users for running scripts that help them automatically perform certain tasks on the site.

The mostly lengthy account has been published on the Get Smart Blog under the title The Grim Reaper has visited Digg. The post lists 86 usernames that were unceremoniously dropped from the site without forewarning. The tone of the author and his commenters, all apparently Digg users (or ex-Digg users) themselves, is dramatic: “So many brave and valiant Diggers…it is a tragedy of unspeakable proportions to see such wasted talent.”

Among those banned was a user named Diggboss who had developed a GreaseMonkey script for checking up on friends to see whether they’ve dugg the items that you’ve submitted or shouted. The script used Digg’s own APIs and didn’t automatically Digg any stories, yet Digg’s Terms of Use vaguely prohibits “automated means to access the Site” and any “organized effort that in any way artificially alters the results of Digg’s services.”

In an official blog post from last week, Jen Burton from Digg suggested that scripts were primarily forbidden because they “place additional load on Digg servers (slowing things down for everyone)”. It’s quite clear, however, that Digg is also concerned with preventing users from gaming the system by recruiting their friends. The Duggboss script may not have automatically submitted stories, but it did help users pursue a strategy of scratching backs for homepage hits (a strategy that ensnared Mark Cuban’s own brother).

Many users are defiant that Digg should dismiss long-time contributors on the grounds that they had run scripts. And some think Digg is shooting itself in the foot by giving users reason to jump ship:

Script? All I have to say about that is WHO CARES! Is Digg doing great in traffic and usage? YES! The site could be a little easier to use if you ask me and if script enables people to use it faster….. so be it! It only works in Digg’s favor and you would think they would understand that. It will be very interesting to see what happens in the next few months. Digg might just become a ghost town and Yahoo Buzz could be the next guru.

But that’s nothing new.

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As a concept, Veritocracy is actually quite simple.  At its heart, social news site pulls together some of the better qualities of Techmeme — targeted stories and related posts to an original story — and Digg. Once you get to the front page, you’re immediately presented with a nice layout of highly-targeted stories on topics ranging from politics and technology to business and entertainment.

The site collects what it deems to be the best perspectives on various subjects from around the Web, groups them together by topic, and lets its users decide which is best through the use of a voting system. As a user votes on different stories, Veritocracy becomes more personalized to that specific user’s tastes. And as long as that engine works well, Veritocracy claims publishers will be able to find the ideal target audience and readers will find stories that fit their interests.”The ultimate objective,” says CEO Lee Hoffman, “is to create a truly meritocratic content distribution system where each article a writer publishes finds its way to the individual readers that will actually want to see it.”

Before that can happen, Veritocracy has a long way to go. Right now, the site is in private beta and is slowly working its way towards a wider release later this year. If you want to check out Veritocracy for yourself, Veritocracy sent us 500 invites for TechCrunch readers. To redeem your invite, type “techcrunchlove” into the invite box, sign up, and start using it.

After trying it for a while, it quickly becomes apparent that if users find reasons to use this site and the company can deliver on its lofty promises, Veritocracy could become a destination for news junkies.

In each category, you’re presented with a story — “Palin takes the stage on night two at the convention” for example — that can be clicked on. Once you click that link, you’ll drill-down into perspectives on the Vice Presidential nominee’s speech last night at the Republican National Convention. Some say it was great, others are more suspect of its success. From there, you can click on the links to be brought to the respective article or you can vote them up or down based on your own opinion on the subject.

As votes start accumulating, Veritocracy promotes the better stories to the top. At the same time, each of your votes is recorded and remembered to help create a more enjoyable experience the next time you come back to the site. In other words, if you continually vote stories by conservative pundits down in the politics section and you tend to enjoy stories that are more “cranky” in the technology section, Veritocracy will tailor your experience based on those votes.

As CEO Hoffman points out, “Veritocracy isn’t a popularity contest, so voting up all of your friends’ content will only cause you to see more of their stuff, and the stuff they like.”

That in mind, the success of Veritocracy depends on the honesty of its users. The name “Veritocracy” is derived from the concept of meritocracy: those stories that deserve to be best will be. If users vote for those perspectives that deserve to be promoted, the site should run as designed: the best stories on each topic will rise to the top, and the greatest number of users will have a personalized experience.  How will Veritocracy fight people trying to game the rankings?  Hoffman explains:

We do this by learning how effective each user on the site is as an editor for you by comparing your vote histories. Unlike other personalization/recommendation systems (think Amazon, and Digg’s new recommendations) our system significantly ramps up the accuracy of these predictions by using a market based design layered over the standard personalization algorithms.

If you submit crap, miscategorize your articles, or even vote for other people’s crap, readers won’t be voting for the same things you are (and may even vote down things you vote up) and thus the the system will uncorrelate you from everyone (or won’t correlate you to them in the first place). This will make sure your content and votes have less chance of effecting what other users see in the future. Of course, a lot of the time “crap” and “quality” are entirely relative, and that’s where the system really shines because it learns to distinguish this for each user, based on the same design principal.

Veritocracy also lets the original authors of stories submit them on different topics. (Veriticracy funnels all stories into consistent topics instead of tags).  After a specific topic is identified, users can upload their own stories, which will then be placed as a perspective on the given topic. Once there, other users can vote it up or down based on its quality and relevance to the topic.

But because so much of Veritocracy’s success relies on its community, it’s tough to say how well it will perform—for now, few even have access to it. But the site has promise. It just needs more participation.

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InvespBlog has published what it claims is an interview with a top Digg user - someone who has a 34% success ratio in getting submitted stories to the home page of Digg. The Digg user isn’t named - he or she says “I have a reputation to withhold” (we know what they meant).

In the interview the user talks a little about how he’s able to get stories to the home page of the Digg news site and drive significant traffic back to the destination, despite the increasing popularity of the site. There isn’t much that will surprise people, the user simply does a lot of networking and reciprocal voting with other top users.

But the user also claims to charge for his services. A submission is $300-$500 based on the “quality of the article,” with no additional “promotion.” If you want your article promoted it’s a flat $700 fee. An additional $500 is charged if it gets to the home page. That’s a grand total of $1,200 for a home page story, and you don’t even get guaranteed results.

Digg knows this kind of manipulation goes on, and wages a never-ending battle to try to keep spamming to a minimum. It seems to have worked in keeping organized spamming schemes from making any real progress. But on an individual level there isn’t much Digg can do to stop top users from selling their influence.

Way back in 2007, Netscape even tried paying top Digg users directly to defect to their new service, so there is no denying that you can make money by being good at spotting a likely popular story.

One thing this tells me is that Digg should strongly consider placing clearly labeled advertisements within the news stories. Even as paid ads they’ll get a ton of traffic and Digg can charge accordingly. TechMeme, a tiny site in comparison, has done this successfully for some time. If Digg can’t stop its users from making a little money on the side, they may as well get in on the game.

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One month after launching its new recommendation system, Digg is already reporting positive results. Digg recommends stories based on other members with similar voting patterns and interests. Chief scientist Anton Kast writes on the Digg Blog:

- Digging activity is up significantly: the total number of Diggs increased 40% after launch.

- The Recommendation Engine is running strong: at any given point in time, the system is generating over 54 Million Recommendations, with the average Digger having nearly 200 Recommendations from an average of 34 “Diggers like you”.

- Friend activity/friends added is up 24%.

- Commenting is up 11% since launch.

Digg’s recommendation engine takes a Last.fm approach to finding people’s whose tastes overlap with yours and then suggesting stories they’ve Dugg up but that you’ve missed. It is collaborative filtering for news.

As Digg becomes more mainstream, it needs technologies such as this to bring it back to its glory days when everybody was interested in the same niche categories. Social recommendations work best when they are extracted from niche communities who are obsessive about one or two topics. Digg started out as a haven for hardcore techies, but has branched out.

The recommendation system is designed to, in effect, help Diggers carve out their own niche communities again. If you happen to like tech industry news, you will see stories from other like-minded Diggers. If you prefer politics or sports, you’ll get those stories. And if you like a combination, the system will grab recommendations from each appropriate bucket.

At least, that is how it is supposed to work in theory. The recommendations seem decent. But I personally haven’t noticed anything that really strikes home. Over time, it should get better.

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When Digg’s Lead Architect Joe Stump took the stage at the Facebook Developer Conference in San Francisco earlier today, something in one of his screen shots caught our attention. He was there to show how users will soon be able to log in to Digg without an account via their Facebook credentials (the new Facebook Connect product). But also included prominently in the screen, but not mentioned by Stump, was an option to log in via OpenID.

Digg founder Kevin Rose promised OpenID integration at a conference in early 2007, but the company has been silent on it since then. Like many other companies, they seemed to enjoy the positive press that the announcement made but were unwilling to schedule the development time to actually implement it.

Facebook Connect isn’t slated to go live until the Fall, and we assume they’ll push OpenID at the same time. We asked OpenID’s David Recordan what he knew - he said he noticed the same thing we did but doesn’t have any additional information on when or if Digg would finally implement the single sign-on solution. We also have an email in to Digg for comment.

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The video above shows a user interface being bucket tested by Google to select (probably randomly determined) users. Earlier today we showed a screen shot of the interface and a video of the search history, recorded by Adrian Pike, the CTO of startup Tatango. This new video, however (also recorded by Pike), shows the full Google search experience with a very Digg-like interface. Users vote search results up or down - a down vote makes it dissapear with a “poof,” an up vote moves the result to the first page.

Google is also testing comments, with linked user names, and others can vote those comments up and down. In effect, this bucket test shows a Google that combines their search algorithm with every important feature of Digg. It’s something they’ve been working on for nearly a year in various iterations, but this is the first time we’ve seen user comments, and the video shows details that you just can’t experience via screen shots.

If feedback on this is positive look for it to be added to the Google Search experimental site where anyone can opt in to use it. It’s still many steps away from being integrated into everyday search on Google, but this shows quite clearly where their head is at - Digg.

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As Digg becomes more mainstream, so are the headlines linked to on its homepage. The once tech-heavy site long ago expanded into other categories such as entertainment, world, and business news. But that change is finally hitting its home page, either because Digg is attracting more mainstream users who are Digging more mainstream stories or it is using other (algorithmic) methods to point its firehouse in the direction of mainstream media. (Comscore shows 15.4 million unique visitors in May, and 6.3 million U.S. visitors in June).

Hitwise released some data today indicating that Digg now sends nearly as much traffic to entertainment sites as it does to news and media sites. As the chart above shows, 21.3 percent of its traffic goes to the former, while 20.7 percent goes to news and media sites. A year ago the gap between the two categories was a 50 percent gap, now it is a 3 percent gap. The traffic sent to entertainment sites as a percentage of Digg’s total outgoing traffic is down 20 percent, while the traffic it pushes to news and media sites is up 16 percent (although both are down since April).

This data confirms a trend that Allen Stern at CenterNetworks noticed last week. Namely, that UK newspapers in particular, like the Guardian, are showing up a lot more often on Digg’s homepage, displacing more familiar tech sites such as Ars Technica, Engadet, and Gizmodo. (When I checked today, about half of the stories on Digg’s homepage linked to traditional news sites). He also speculated whether this meant that Digg is trying to sell itself to the Guardian, which bought the blog network that owns PaidContent last week for an estimated $30 million.

That seems like a stretch, but showing that it can drive more traffic to traditional media sites would certainly make Digg more appealing to any potential acquirer. There has been no shortage of acquisition rumors over the years, but it would make more sense for a semi-neutral technology company like Microsoft or Google to make a bid than a media company with ts own properties to promote.

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Digg has released some materials around their new Recommendation Engine, which we wrote about last night, and say that it will be released this week. Two overview videos are below, including an interview with Digg Lead Scientist Anton Kast. We’ve also included the text of a white paper on the Recommendation Engine.

The Digg Recommendation Engine
People love Digg because it’s a place to discover and share great content from around
the Web. The Digg homepage always has the most popular stories, but many Digg
users find their content in the Upcoming section, which gets over 15,000 new stories a
day. To help users filter this enormous amount of content, we have created a new
feature: The Digg Recommendation Engine.

When you Digg a story, you tell the Recommendation Engine two things: that you
recommend the story to other users and, less obviously, that the users who Dugg the
story before you are good at finding content. The Recommendation Engine keeps track
of users who Dugg particular stories before you did, and it recommends you the stories
they Dugg. The more content you Digg, the smarter the Recommendation Engine
becomes.

Finding Diggers Like You
The Digg Recommendation Engine uses your Digg history over the last thirty days to
make Recommendations. (You can see the number of items you have Dugg over the
last month on the right-hand side of the Recommended view.) Every time you Digg a
story, the Engine matches you with other Diggers who Dugg the same story, and keeps
track of all your Diggs in common with them.

When it’s time to calculate your Recommendations, the Engine draws from this pool of
matched Diggers. For each matched Digger, it computes a correlation coefficient
between you and them. It then picks a cutoff for this correlation coefficient, and the
Diggers who make the cut are called “Diggers Like You.”

It’s easy to understand how the correlations are calculated. For each user with whom
you Dugg something in common, the Engine determines how many stories the two of
you Dugg in common, and divides that number by the total number of stories you or they
Dugg. The ratio is a correlation coefficient, a number between zero and one (zero if you
and the other user never agreed; one if you always did). Such a ratio is sometimes
called a “Jaccard coefficient.”

This scheme automatically accounts for the overall level of Digging activity. If another
user Diggs a lot, they have to agree with you on many stories to become a Digger Like
You. If another user Diggs rarely, then a small amount of agreement can suffice.
2
From Diggers Like You to Recommendations
Once the Engine has determined your Diggers Like You, your Recommendations consist
of stories that your Diggers Like You have already Dugg, minus the stories you already
Dugg or Buried. There are some extra steps, like the diversity rules and the
promotability constraint described below, but this is the basic idea.

Recommendations are always displayed together with your Diggers Like You and their
compatibility percentages. These percentages are just correlation coefficients. You may
notice that you are more compatible with a user that has fewer Recommendations than a
user with less compatibility but with more Recommendations. This is because although
you have Dugg more items in common with the more compatible user, that user has not
Dugg as much.

The Recommendations you get from any particular user will come from topics (such as
Technology or World News) where you have a shared Digging history. We figure that
two users may have similar interests in a subject like ‘playable web games’, but one
person might be into politics while the other follows celebrity gossip. So we actually
compute correlations, Diggers Like You, and compute Recommendations in several
collections of topics independently.

Promotable Stories
Since the Recommendation Engine works only with Upcoming stories, all the stories you
get from the Recommendation Engine are “promotable”, meaning that they are recent
enough to be eligible for the Digg homepage but haven’t appeared there yet. This
means that whenever you Digg one of your Recommendations, you are helping select
stories for the front page of Digg!

Diversity
Just like stories on the homepage, we want your Recommendations to be diverse: a
balanced number of stories, not all on the same topic, and not all Dugg by the same
people.

To make sure that your Recommendations are diverse, the Engine imposes limits that
keep things from getting too focused. It makes sure that no one Digger Like You
determines too many of your stories. It attempts to make your Recommendations reflect
the spectrum of topics that you’ve Dugg in the past, and it adjusts the compatibility cutoff
for Diggers Like You so you don’t get too many or too few stories.

The Engine also limits the influence of any single one of your Diggs. For instance, if you
are Digg number 1,000 on a popular story, you will have 999 similar users from that one
Digg alone, and those users are not necessarily more compatible with you than the two
3
or three who may have Dugg a less popular story you also liked. The Engine limits the
total pool of users you can get from a single Digg to balance things out.

We hope you enjoy using the Recommendation Engine and look forward to helping you
uncover even more great stories on Digg!
Digg on!
Anton Kast – Lead Scientist Digg

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Digg competitor Mixx just launched an extension to its groups feature that founder Chris McGill describes as “Ning for social media”.

Users can now set up Mixx community sites on their own subdomains (see ours here). Administrators have the power to brand them visually, post editorial content, and even make some revenue off advertisements. Others can join as members and begin submitting items as they would regularly on Mixx. All submissions (stories, images, and videos) can be made just to a particular community, or to the Mixx site as a whole as well.

This release is more akin to Reddit’s hosted “create a Reddit” service than it is to Reddit’s new open source offering since Mixx communities are hosted and can only be rebranded to a limited extent (with custom logos and color schemes).

Just as the standard Mixx experience is divided into verticals like Entertainment, Science and Sports, communities can deploy their own tabs for niche topics. The TechCrunch community, for example, has been seeded with tabs for “Obtaining Funding”, “Creating the Dream Team”, and “Revenue Models”. To keep each of these categories alive - and therefore your community members engaged - admins can set tags that will automatically import relevant items from the main Mixx sharing stream (”google”, “arrington”, “techcrunch”, “twitter”, “yahoo” have been set as tags in our case).

Communities also come equipped with a message board and a “member lounge” that provides community overview information such as activity stats, member lists, and awards for top submitters.

Social media fanatics will enjoy this new ability to carve out their own alcoves in Mixx. I’d really like to see Mixx take the next step and allow for a completely rebranded experience so that web publishers the net over can incorporate user contributed content seamlessly into their sites. This would entail proper domain masking and thorough CSS and HTML customization, as you’d find on KickApps. Then Mixx could really claim to compete with the likes of Ning and the other social networking platforms.

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It amazes me that people actually talk to Loren Feldman’s puppet and treat it like a real interview. Example above: this interview with Kevin Rose starts off innocently enough, but goes down hill from there. The only real news value in the story is that Digg’s still working on that recommendation feature. The high entertainment value, including a few seconds about Kevin’s dating life, make for the lack of actual news though.

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Facebook will announce later today Facebook Connect, which has similar functionality to MySpace Data Availability, announced ju