On Saturday, Charlene Li discussed how social networks are to be "like air", integrated into all the Web sites we visit. She painted a future whereby your friends and who you are as an individual would dictate the content and delivery of your Web experience. Just how to make that Web experience social, but in the right way, is a dilemma services are encountering, including executives at Pandora, Strands and Blip.TV, who talked at length today at the SXSW Interactive conference about how much power the community, and recommendations, should weigh on their products' experience. They also debated whether editorial recommendations had a place, and could be trusted.

When an application or service becomes social, the recommendations one gains from the community and your fellow friends hold significant weight. On Amazon, you might be told to purchase a book or DVD. On Pandora, you might start hearing music from a new artist. And Blip.tv? Well, they're still looking for the right solution, before they start tossing out videos of dogs on skateboards, due simply to popularity, as CEO Mike Hudack said today.

When done well, algorithmically generated recommendations can promote user action, including purchases, which then in turn makes it tempting to integrate social recommendations in practically every element of the eCommerce engine, the panelists agreed.

"Amazon is the quintessential recommender of the influential purchase," said Alex Hillman of Independents Hall. "If I am logged in and it knows what I bought before, it starts recommending things. I do trust it, and it is surprisingly accurate."

But Trevor Legwinski, who runs Marketing and Business Development for Strands, cautioned against showing too many options throughout a service.

"On the eCommerce side of things, (we are challenged) with how we increase our revenue, and what could provide a better consumer experience. But from an eCommerce perspective, if you give them (users) too many options, they will leave the site," he said.

Sites like Amazon.com, Netflix, Pandora, Last.fm and many others rely on the wisdom of crowds to try and figure out your own interests. And sites of all types have been asking you for more and more information for decades, harkening back to some of the most invasive registration regiments out there, around Web dating sites. And even if you put "a crapload" of data in, as Hillman called it, you probably should just save the time and go out on a date instead.

But these products are each working on finding the right mix of input from the community, and that of those hired by the company. Tom Conrad, CTO of Pandora, called it blending expert influence with community filtering.

"Collaborative filtering comes from purchase behavior and community behavior," Conrad said. "But it does have a self-reinforcing characteristic to it. If you tell it people that buy Nine Inch Nails also buy Ministry, it is reinforcing and it is hard to break out of that pattern, and it is even harder with the long tail where there is not enough data to build recommendations, so you have to build systems around factual information around the product."

One of the more visible recent developments in the world of recommendations came from Twitter, who seemingly hand-selected a small number of people to be recommended accounts. The move, which has seen total followers to these accounts skyrocket as the service dramatically grew in visibility, has had many influential users questioning the practice, and others begging to be included.

Today's panel questioned if the uproar was justifiable, considering there was no science behind the recommended list. And while they questioned if those selected offered new users a representative view of the microblogging service, the concept of an "editorial recommendation" was not dismissed outright - even while some panelists had avoided editorial selection in their own products.

"We don't publish top ten lists," said Conrad. "There is no way to find out what songs get the most thumbs up. We never say there are interesting bands to check out, as it's about you, not us. It's about what you think is cool."

Comments around the Twitter signup process generally recommended the service would be better served to ask for more questions up front, and try to leverage their search engine to show experts on topics the new users claimed interest in.

"Twitter could solve that problem if you could pull up other Twitterers who match those terms," Hillman said.

The panel concluded in agreement that the human experience, and recommendations from machines that start with human input were considered "the richest", and it was agreed that the human element would never "go away", but that engines needed to continue to improve to offer a smoother experience for services that relied on the wisdom of others.

"Any time you have a problem with a multiplicity of potential solutions, you have an opportunity as a developer for a recommendation solution to bring an answer to that problem," said Conrad. "Anywhere you have lots of potential solutions, you can narrow it down to one solution that is an answer."

My major driver for attending the SXSW Interactive conference this week was to participate in a panel, held this morning, discussing how to find the best and most interesting content on the Web, getting beyond simple aggregation. Sharing the stage with four very interesting peers, from Marshall Kirkpatrick of ReadWriteWeb and Gabe Rivera of Techmeme to Melanie Baker of PostRank and Micah Baldwin of Lijit, we discussed both our secrets and our motivations for getting to the highest-quality content quickly. In my opinion, the "right" way to find the best content wasn't so much a workflow discussion or a tools discussion, but one of motivation - what drives you to take the effort to find it?

For Marshall and me, as bloggers, we are very interested in finding new stories and product releases ahead of others. Gabe, working with his tool's algorithm, hoped to find relevant news, partially defined by the number and strength of relevant links and content. Micah and Melanie both discussed how their products aim to do the dirty work of chewing through the vast amount of information to find the "best" and "most influential" sources and content. And for the many different people sitting in the room, each had their own pull - as we discussed what was driving their need to be constantly updated, and it was clear there was a dividing line - did you want to find it when it was brand new, or could you rely on recommendations from friends and peers?

I've talked quite a bit on the blog about the tools I use to find both new content and recommended, trusted content. Partially recapping from the panel, here's what we discussed:

To Find Brand-New Content

Google Reader is still the very best item I use every day to take in news from hundreds of different feeds, be they on technology, sports, business or social media. RSS powers my desire for immediacy, and Google Reader helps me both discover data only minutes after it is posted, but also share it and start to act as an information filter.

Referral Logs are a sneaky way to find new services. It's how I found many services that were in development, but had not debuted, including ReadBurner, Assetbar, Shyftr and others. Developers often check out stories with their own tools and due diligence can uncover scoops.

Search Alerts through Google, Twitter, BackType and other content repositories can give you a heads up when items you are most interested in are mentioned.

Old School Tools still are great ways to get connected. If you can post your phone number to your blog, do it. Make yourself available to content producers and entrepreneurs, so they can reach you with news.

To Find Top-Quality Trusted Content

Google Reader Shared Items let others who you trust act as information filters and pass along the very best of those sites they are using from around the Web.

FriendFeed's Best of Day tools let you find the most important stories, as determined by social activity, including likes and comments, and can be segmented by all those you follow, or lists, meaning you can see what a subsegment of your friends are finding most interesting in a time period, be it 1 day, 7 or a month.

TechFuga and Techmeme are two aggregators aimed to get high-quality content in the technology space, and other non-tech verticals are being built out, including the family of sites from the Ballhype crew, including Showhype, BeltwayBlips and the like.

Twitter Search and Leaderboards like TweetMeme let you see what are the most distributed tweets and links.

RSSmeme and ReadBurner help display the top shared Google Reader items of the day.

There's much, much more of course. We've talked about my social media consumption workflow before, and the way I do it may differ both from how you do, and from the way others on the panel explained their process. You can see additional coverage of the presentation from this morning here: SheGeeks: Beyond Content Aggregation – Filtering Services, Popular, & Relevant Content and Beyond Aggregation — Finding the Web’s Best Content at SXSW. An outstanding thread on FriendFeed, sparked by Eric Berlin, can be found here: “Monday, bright-ish and early-ish at Austin's SXSW, session called Beyond Aggregation - Finding the Web's Best Content”.

By Jesse Stay of Stay N' Alive (Twitter/FriendFeed)

Today, Facebook announced they are now making it possible for anyone to open up their status updates and more, to the world. This means that by going into your privacy settings on Facebook and selecting "everyone" on various profile options, Google can now index it, non-friends are able to see it, and it puts Facebook "face-to-face" in the "worldwide conversation" with Twitter. Yes, Facebook has just killed the walled garden.
Read more by Jesse Stay at Stay N' Alive.

Even as many voters sat on pins and needles, the 2008 presidential election was among the easiest to predict, according to Nate Silver of FiveThirtyEight.com, whose site skyrocketed to stardom amid high visibility throughout the primary and general election season last year, as he took a thorough background in statistical analysis and focused on the world of politics, hoping to improve the accuracy of polls and predictive analysis. In his comments on a keynote at the SXSW Interactive conference today, he said media outlets relied too much on most recent news, and could improve their prognoses if they instead turned to historical statistics and trend data.

Nate said he started FiveThirtyEight.com "out of frustration" with the traditional media properties, including CNN, MSNBC and Fox News. He said their coverage "wasn't empirically valid and correct," adding, "polls were too much of the narrative and they were taken too seriously as they were poorly conducted and interpreted."

Armed with a history of crunching baseball statistics to predict how well players would perform in the future from his time with the Baseball Prospectus, Nate tried to spot irregularities in polling or find variables that indicated how voters in each state were likely to trend which most pollsters were missing. One example included how in the Appalachian region, voters who declined to state their ethnicity, choosing to instead be labeled as "American", were doing so as a badge of pride, but also indicated a level of "redneckness," as he put it.

Like with baseball, Nate called the political process a long season, where largest trends were not swayed by an individual game's data, or by a single primary.

"You don't get that much information at once. A puzzle gets solved a little at a time," Nate said. "People are trained to over-react to these kinds of things, and I would urge patience."

Having successfully predicted the 2008 elections more accurately than practically anybody else out there, Nate is now being courted to try and solve a wide array of other issues, ranging from predicting the Academy Awards (which was partially successful), to predicting economics. As could be expected, he was asked to provide his thoughts on the economic slowdown that has effected everyone, and how long it would be until potential voters started to blame the Obama administration, instead of the Bush administration.

"We haven't had a situation like this in the modern era," Nate said. "People are really scared, and they don't see the light at the end of the tunnel. You have people who are very pessimistic about the future of the country, but Obama has great approval ratings. Usually that doesn't happen. There is a kind of grace period of three to six months, and after this grace period, of about 18 months, people assign him as much blame as they would Bush for the economy, so he needs the economy to turn around sooner, rather than later."

But even armed with as much data and talent as he has, Nate recognizes that other factors are in play. Baseball players can get injured, and "you can only expect a human to do what they do what they were doing so many times," he said, adding, "in baseball, everything in the last 100 years is 99.9% accurate. The real world is not like that."

Speaking of not predicting the real world, the term FiveThirtyEight, which refers to the number of electoral votes available in a presidential election, may need to change, should Washington DC gain representation in Congress, throwing all the numbers off. Should that happen, Nate just may have to change his URL.