Learning, and Profiting, from Online Friendships

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He figures the recommendation would have steered 5 million to 15 million new followers his way within two years and that many would have made their way to his company's Web site. "If 10% click on a link [to Mahalo] once a month," he writes in an e-mail, "you have about 1 million visits a year. ... I'd pay 5 cents for a follower." Lots of businesses, he says, could benefit from such followings. An airline such as JetBlue could offer discounts to the first 1,000 people who respond and "never [have] another empty seat."

While Calacanis tries to build crowds, advertisers are more interested in understanding individuals. Decoding friendship, many believe, could be the key to getting consumers' attention. Historically, this wasn't so hard. Information was in short supply, and by comparison, time was cheap. Not long ago millions waited through entire newscasts just to learn who won a game or what tomorrow's weather would be. This was ideal for advertisers: They had a captive audience.

Now we're swimming in information. We can call up nearly every bit of news, music, and entertainment we want on demand. In fact, there's so much of it that we need filters to block the boring or irrelevant stuff and help us find the bits we need or desire. This has created what many call the "Attention Economy." Says Bernardo A. Huberman, director of the Information Dynamics Laboratory at Hewlett-Packard: "The value of most information has collapsed to zero. The only scarce resource is attention." So how do we figure out where to direct it?

The easiest way is to get tips from friends. They're our trusted sources. At least a few of them know us better than any algorithm ever could. Little surprise, then, that the companies most eager to command our attention are studying which friends we listen to. Online friendship is a hot focus for Facebook, Google, and Yahoo. They joust to hire leading sociologists, anthropologists, and microeconomists from MIT, Harvard, and Berkeley. Microsoft just established a research division focused on social sciences in Cambridge, Mass.

Statistically, friends tend to behave alike. A couple of years ago researchers at Yahoo found that if someone clicked on an online ad, the people on his or her instant chat buddy list, when served the same ad, were three to four times more likely than average to click on it. It makes sense. Friends share interests.

But it raised lots of questions. Which types of friends have the most meaningful correlations with each other? People have always confided in a small circle of intimates, often only two or three. They've also had wider circles of experts for specific advice, whether on cars or cooking. Then there's a broader circle of acquaintances whose opinions count far less but who can still generate buzz about a new restaurant or senatorial candidate. By studying patterns of interactions on networks—often scrutinizing us only as anonymous bits of data—researchers are working to predict which friends we trust and which we pay attention to in each area of our lives. The data can be hard to interpret, says danah boyd, a Berkeley PhD who just signed on at Microsoft Research. (She changed her name to lower case). "You may e-mail your mother less frequently than a colleague, but it's not that she's trusted less."

In an office above Palo Alto's University Avenue, a lean 32-year-old PhD from MIT's Media Lab pores over the data connecting millions of dots. Cameron A. Marlow, a research scientist at Facebook, has perhaps the greatest lab in history for studying friendship. He can study social media communications including wall posts, shared photos, pokes, and friend requests among 200 million people.

IGNORING THE ADS

For all its popularity, Facebook has yet to prove itself as an advertising platform. Visitors, it seems, focus on their friends and pay scant attention to ads. Few click on them, and advertisers pay pennies for page views. Consequently, Facebook, with its estimated revenue of $300 million this year, brings in scarcely a dime a month per member.

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