Number of words – 3,942<\/p>\n\n\n\n
If Facebook were a country, a conceit that founder Mark Zuckerberg has entertained in public, its 900 million members would make it the third largest in the world.<\/p>\n\n\n\n
It would far outstrip any regime past or present in how intimately it records the lives of its citizens. Private conversations, family photos, and records of road trips, births, marriages, and deaths all stream into the company\u2019s servers and lodge there. Facebook has collected the most extensive data set ever assembled on human social behavior. Some of your personal information is probably part of it.<\/p>\n\n\n\n
Heading Facebook\u2019s effort to figure out what can be learned from all our data is Cameron Marlow, a tall 35-year-old who until recently sat a few feet away from \u00adZuckerberg. The group Marlow runs has escaped the public attention that dogs Facebook\u2019s founders and the more headline-grabbing features of its business. Known internally as the Data Science Team, it is a kind of Bell Labs for the social-networking age. The group has 12 researchers\u2014but is expected to double in size this year. They apply math, programming skills, and social science to mine our data for insights that they hope will advance Facebook\u2019s business and social science at large. Whereas other analysts at the company focus on information related to specific online activities, Marlow\u2019s team can swim in practically the entire ocean of personal data that Facebook maintains. Of all the people at Facebook, perhaps even including the company\u2019s leaders, these researchers have the best chance of discovering what can really be learned when so much personal information is compiled in one place.<\/p>\n\n\n\n
Even as Facebook has embedded itself into modern life, it hasn\u2019t done that much with what it knows about us. Its stash of data looms like an oversize shadow. Everyone has a feeling that this resource will yield something big, but nobody knows quite what.<\/p>\n\n\n\n
Facebook has all this information because it has found ingenious ways to collect data as people socialize. Users fill out profiles with their age, gender, and e-mail address; some people also give additional details, such as their relationship status and mobile-phone number. A redesign last fall introduced profile pages in the form of time lines that invite people to add historical information such as places they have lived and worked. Messages and photos shared on the site are often tagged with a precise location, and in the last two years Facebook has begun to track activity elsewhere on the Internet, using an addictive invention called the \u201cLike\u201d button. It appears on apps and websites outside Facebook and allows people to indicate with a click that they are interested in a brand, product, or piece of digital content. Since last fall, Facebook has also been able to collect data on users\u2019 online lives beyond its borders automatically: in certain apps or websites, when users listen to a song or read a news article, the information is passed along to Facebook, even if no one clicks \u201cLike.\u201d Within the feature\u2019s first five months, Facebook catalogued more than five billion instances of people listening to songs online. Combine that kind of information with a map of the social connections Facebook\u2019s users make on the site, and you have an incredibly rich record of their lives and interactions.<\/p>\n\n\n\n
\u201cThis is the first time the world has seen this scale and quality of data about human communication,\u201d Marlow says with a characteristically serious gaze before breaking into a smile at the thought of what he can do with the data. For one thing, Marlow is confident that exploring this resource will revolutionize the scientific understanding of why people behave as they do. His team can also help Facebook influence our social behavior for its own benefit and that of its advertisers. This work may even help Facebook invent entirely new ways to make money.<\/p>\n\n\n\n
Contagious Information<\/p>\n\n\n\n
Marlow eschews the collegiate programmer style of Zuckerberg and many others at Facebook, wearing a dress shirt with his jeans rather than a hoodie or T-shirt. Meeting me shortly before the company\u2019s initial public offering in May, in a conference room adorned with a six-foot caricature of his boss\u2019s dog spray-painted on its glass wall, he comes across more like a young professor than a student. He might have become one had he not realized early in his career that Web companies would yield the juiciest data about human interactions.<\/p>\n\n\n\n
In 2001, undertaking a PhD at MIT\u2019s Media Lab, Marlow created a site called Blogdex that automatically listed the most \u201ccontagious\u201d information spreading on weblogs. Although it was just a research project, it soon became so popular that Marlow\u2019s servers crashed. Launched just as blogs were exploding into the popular consciousness and becoming so numerous that Web users felt overwhelmed with information, it prefigured later aggregator sites such as Digg and Reddit. But Marlow didn\u2019t build it just to help Web users track what was popular online. Blogdex was intended as a scientific instrument to uncover the social networks forming on the Web and study how they spread ideas. Marlow went on to Yahoo\u2019s research labs to study online socializing for two years. In 2007 he joined Facebook, which he considers the world\u2019s most powerful instrument for studying human society. \u201cFor the first time,\u201d Marlow says, \u201cwe have a microscope that not only lets us examine social behavior at a very fine level that we\u2019ve never been able to see before but allows us to run experiments that millions of users are exposed to.\u201d<\/p>\n\n\n\n
Marlow\u2019s team works with managers across Facebook to find patterns that they might make use of. For instance, they study how a new feature spreads among the social network\u2019s users. They have helped Facebook identify users you may know but haven\u2019t \u201cfriended,\u201d and recognize those you may want to designate mere \u201cacquaintances\u201d in order to make their updates less prominent. Yet the group is an odd fit inside a company where software engineers are rock stars who live by the mantra \u201cMove fast and break things.\u201d Lunch with the data team has the feel of a grad-student gathering at a top school; the typical member of the group joined fresh from a PhD or junior academic position and prefers to talk about advancing social science than about Facebook as a product or company. Several members of the team have training in sociology or social psychology, while others began in computer science and started using it to study human behavior. They are free to use some of their time, and Facebook\u2019s data, to probe the basic patterns and motivations of human behavior and to publish the results in academic journals\u2014much as Bell Labs researchers advanced both AT&T\u2019s technologies and the study of fundamental physics.<\/p>\n\n\n\n
It may seem strange that an eight-year-old company without a proven business model bothers to support a team with such an academic bent, but \u00adMarlow says it makes sense. \u201cThe biggest challenges Facebook has to solve are the same challenges that social science has,\u201d he says. Those challenges include understanding why some ideas or fashions spread from a few individuals to become universal and others don\u2019t, or to what extent a person\u2019s future actions are a product of past communication with friends. Publishing results and collaborating with university researchers will lead to findings that help Facebook improve its products, he adds.<\/p>\n\n\n\n
For one example of how Facebook can serve as a proxy for examining society at large, consider a recent study of the notion that any person on the globe is just six degrees of separation from any other. The best-known real-world study, in 1967, involved a few hundred people trying to send postcards to a particular Boston stockholder. Facebook\u2019s version, conducted in collaboration with researchers from the University of Milan, involved the entire social network as of May 2011, which amounted to more than 10 percent of the world\u2019s population. Analyzing the 69 billion friend connections among those 721 million people showed that the world is smaller than we thought: four intermediary friends are usually enough to introduce anyone to a random stranger. \u201cWhen considering another person in the world, a friend of your friend knows a friend of their friend, on average,\u201d the technical paper pithily concluded. That result may not extend to everyone on the planet, but there\u2019s good reason to believe that it and other findings from the Data Science Team are true to life outside Facebook. Last year the Pew Research Center\u2019s Internet & American Life Project found that 93 percent of Facebook friends had met in person. One of Marlow\u2019s researchers has developed a way to calculate a country\u2019s \u201cgross national happiness\u201d from its Facebook activity by logging the occurrence of words and phrases that signal positive or negative emotion. Gross national happiness fluctuates in a way that suggests the measure is accurate: it jumps during holidays and dips when popular public figures die. After a major earthquake in Chile in February 2010, the country\u2019s score plummeted and took many months to return to normal. That event seemed to make the country as a whole more sympathetic when Japan suffered its own big earthquake and subsequent tsunami in March 2011; while Chile\u2019s gross national happiness dipped, the figure didn\u2019t waver in any other countries tracked (Japan wasn\u2019t among them). Adam Kramer, who created the index, says he intended it to show that Facebook\u2019s data could provide cheap and accurate ways to track social trends\u2014methods that could be useful to economists and other researchers.<\/p>\n\n\n\n
Other work published by the group has more obvious utility for Facebook\u2019s basic strategy, which involves encouraging us to make the site central to our lives and then using what it learns to sell ads. An early study looked at what types of updates from friends encourage newcomers to the network to add their own contributions. Right before Valentine\u2019s Day this year a blog post from the Data Science Team listed the songs most popular with people who had recently signaled on Facebook that they had entered or left a relationship. It was a hint of the type of correlation that could help Facebook make useful predictions about users\u2019 behavior\u2014knowledge that could help it make better guesses about which ads you might be more or less open to at any given time. Perhaps people who have just left a relationship might be interested in an album of ballads, or perhaps no company should associate its brand with the flood of emotion attending the death of a friend. The most valuable online ads today are those displayed alongside certain Web searches, because the searchers are expressing precisely what they want. This is one reason why Google\u2019s revenue is 10 times Facebook\u2019s. But Facebook might eventually be able to guess what people want or don\u2019t want even before they realize it.<\/p>\n\n\n\n
Recently the Data Science Team has begun to use its unique position to experiment with the way Facebook works, tweaking the site\u2014the way scientists might prod an ant\u2019s nest\u2014to see how users react. Eytan Bakshy, who joined Facebook last year after collaborating with Marlow as a PhD student at the University of Michigan, wanted to learn whether our actions on Facebook are mainly influenced by those of our close friends, who are likely to have similar tastes. That would shed light on the theory that our Facebook friends create an \u201cecho chamber\u201d that amplifies news and opinions we have already heard about. So he messed with how Facebook operated for a quarter of a billion users. Over a seven-week period, the 76 million links that those users shared with each other were logged. Then, on 219 million randomly chosen occasions, Facebook prevented someone from seeing a link shared by a friend. Hiding links this way created a control group so that Bakshy could assess how often people end up promoting the same links because they have similar information sources and interests.<\/p>\n\n\n\n
He found that our close friends strongly sway which information we share, but overall their impact is dwarfed by the collective influence of numerous more distant contacts\u2014what sociologists call \u201cweak ties.\u201d It is our diverse collection of weak ties that most powerfully determines what information we\u2019re exposed to.<\/p>\n\n\n\n
That study provides strong evidence against the idea that social networking creates harmful \u201cfilter bubbles,\u201d to use activist Eli Pariser\u2019s term for the effects of tuning the information we receive to match our expectations. But the study also reveals the power Facebook has. \u201cIf [Facebook\u2019s] News Feed is the thing that everyone sees and it controls how information is disseminated, it\u2019s controlling how information is revealed to society, and it\u2019s something we need to pay very close attention to,\u201d Marlow says. He points out that his team helps Facebook understand what it is doing to society and publishes its findings to fulfill a public duty to transparency. Another recent study, which investigated which types of Facebook activity cause people to feel a greater sense of support from their friends, falls into the same category.<\/p>\n\n\n\n
But Marlow speaks as an employee of a company that will prosper largely by catering to advertisers who want to control the flow of information between its users. And indeed, Bakshy is working with managers outside the Data Science Team to extract advertising-related findings from the results of experiments on social influence. \u201cAdvertisers and brands are a part of this network as well, so giving them some insight into how people are sharing the content they are producing is a very core part of the business model,\u201d says Marlow.<\/p>\n\n\n\n
Facebook told prospective investors before its IPO that people are 50 percent more likely to remember ads on the site if they\u2019re visibly endorsed by a friend. Figuring out how influence works could make ads even more memorable or help Facebook find ways to induce more people to share or click on its ads.<\/p>\n\n\n\n
Marlow says his team wants to divine the rules of online social life to understand what\u2019s going on inside Facebook, not to develop ways to manipulate it. \u201cOur goal is not to change the pattern of communication in society,\u201d he says. \u201cOur goal is to understand it so we can adapt our platform to give people the experience that they want.\u201d But some of his team\u2019s work and the attitudes of Facebook\u2019s leaders show that the company is not above using its platform to tweak users\u2019 behavior. Unlike academic social scientists, Facebook\u2019s employees have a short path from an idea to an experiment on hundreds of millions of people.<\/p>\n\n\n\n
In April, influenced in part by conversations over dinner with his med-student girlfriend (now his wife), Zuckerberg decided that he should use social influence within Facebook to increase organ donor registrations. Users were given an opportunity to click a box on their Timeline pages to signal that they were registered donors, which triggered a notification to their friends. The new feature started a cascade of social pressure, and organ donor enrollment increased by a factor of 23 across 44 states.<\/p>\n\n\n\n
Marlow\u2019s team is in the process of publishing results from the last U.S. midterm election that show another striking example of Facebook\u2019s potential to direct its users\u2019 influence on one another. Since 2008, the company has offered a way for users to signal that they have voted; Facebook promotes that to their friends with a note to say that they should be sure to vote, too. Marlow says that in the 2010 election his group matched voter registration logs with the data to see which of the Facebook users who got nudges actually went to the polls. (He stresses that the researchers worked with cryptographically \u201canonymized\u201d data and could not match specific users with their voting records.)<\/p>\n\n\n\n
This is just the beginning. By learning more about how small changes on Facebook can alter users\u2019 behavior outside the site, the company eventually \u201ccould allow others to make use of Facebook in the same way,\u201d says Marlow. If the American Heart Association wanted to encourage healthy eating, for example, it might be able to refer to a playbook of Facebook social engineering. \u201cWe want to be a platform that others can use to initiate change,\u201d he says.<\/p>\n\n\n\n
Advertisers, too, would be eager to know in greater detail what could make a campaign on Facebook affect people\u2019s actions in the outside world, even though they realize there are limits to how firmly human beings can be steered. \u201cIt\u2019s not clear to me that social science will ever be an engineering science in a way that building bridges is,\u201d says Duncan Watts, who works on computational social science at Microsoft\u2019s recently opened New York research lab and previously worked alongside Marlow at Yahoo\u2019s labs. \u201cNevertheless, if you have enough data, you can make predictions that are better than simply random guessing, and that\u2019s really lucrative.\u201d<\/p>\n\n\n\n
Doubling Data<\/p>\n\n\n\n
Like other social-Web companies, such as Twitter, Facebook has never attained the reputation for technical innovation enjoyed by such Internet pioneers as Google. If Silicon Valley were a high school, the search company would be the quiet math genius who didn\u2019t excel socially but invented something indispensable. Facebook would be the annoying kid who started a club with such social momentum that people had to join whether they wanted to or not. In reality, Facebook employs hordes of talented software engineers (many poached from Google and other math-genius companies) to build and maintain its irresistible club. The technology built to support the Data Science Team\u2019s efforts is particularly innovative. The scale at which Facebook operates has led it to invent hardware and software that are the envy of other companies trying to adapt to the world of \u201cbig data.\u201d<\/p>\n\n\n\n
In a kind of passing of the technological baton, Facebook built its data storage system by expanding the power of open-source software called Hadoop, which was inspired by work at Google and built at Yahoo. Hadoop can tame seemingly impossible computational tasks\u2014like working on all the data Facebook\u2019s users have entrusted to it\u2014by spreading them across many machines inside a data center. But Hadoop wasn\u2019t built with data science in mind, and using it for that purpose requires specialized, unwieldy programming. Facebook\u2019s engineers solved that problem with the invention of Hive, open-source software that\u2019s now independent of Facebook and used by many other companies. Hive acts as a translation service, making it possible to query vast Hadoop data stores using relatively simple code. To cut down on computational demands, it can request random samples of an entire data set, a feature that\u2019s invaluable for companies swamped by data. Much of Facebook\u2019s data resides in one Hadoop store more than 100 petabytes (a million gigabytes) in size, says Sameet Agarwal, a director of engineering at Facebook who works on data infrastructure, and the quantity is growing exponentially. \u201cOver the last few years we have more than doubled in size every year,\u201d he says. That means his team must constantly build more efficient systems.<\/p>\n\n\n\n
All this has given Facebook a unique level of expertise, says Jeff Hammerbacher, Marlow\u2019s predecessor at Facebook, who initiated the company\u2019s effort to develop its own data storage and analysis technology. (He left Facebook in 2008 to found Cloudera, which develops Hadoop-based systems to manage large collections of data.) Most large businesses have paid established software companies such as Oracle a lot of money for data analysis and storage. But now, big companies are trying to understand how Facebook handles its enormous information trove on open-source systems, says Hammerbacher. \u201cI recently spent the day at Fidelity helping them understand how the \u2018data scientist\u2019 role at Facebook was conceived \u2026 and I\u2019ve had the same discussion at countless other firms,\u201d he says.<\/p>\n\n\n\n
As executives in every industry try to exploit the opportunities in \u201cbig data,\u201d the intense interest in Facebook\u2019s data technology suggests that its ad business may be just an offshoot of something much more valuable. The tools and techniques the company has developed to handle large volumes of information could become a product in their own right.<\/p>\n\n\n\n
Mining for Gold<\/p>\n\n\n\n
Facebook needs new sources of income to meet investors\u2019 expectations. Even after its disappointing IPO, it has a staggeringly high price-to-earnings ratio that can\u2019t be justified by the barrage of cheap ads the site now displays. Facebook\u2019s new campus in Menlo Park, California, previously inhabited by Sun Microsystems, makes that pressure tangible. The company\u2019s 3,500 employees rattle around in enough space for 6,600. I walked past expanses of empty desks in one building; another, next door, was completely uninhabited. A vacant lot waited nearby, presumably until someone invents a use of our data that will justify the expense of developing the space.<\/p>\n\n\n\n
One potential use would be simply to sell insights mined from the information. DJ Patil, data scientist in residence with the venture capital firm Greylock Partners and previously leader of LinkedIn\u2019s data science team, believes Facebook could take inspiration from Gil Elbaz, the inventor of Google\u2019s AdSense ad business, which provides over a quarter of Google\u2019s revenue. He has moved on from advertising and now runs a fast-growing startup, Factual, that charges businesses to access large, carefully curated collections of data ranging from restaurant locations to celebrity body-mass indexes, which the company collects from free public sources and by buying private data sets. Factual cleans up data and makes the result available over the Internet as an on-demand knowledge store to be tapped by software, not humans. Customers use it to fill in the gaps in their own data and make smarter apps or services; for example, Facebook itself uses Factual for information about business locations. Patil points out that Facebook could become a data source in its own right, selling access to information compiled from the actions of its users. Such information, he says, could be the basis for almost any kind of business, such as online dating or charts of popular music. Assuming Facebook can take this step without upsetting users and regulators, it could be lucrative. An online store wishing to target its promotions, for example, could pay to use Facebook as a source of knowledge about which brands are most popular in which places, or how the popularity of certain products changes through the year.<\/p>\n\n\n\n
Hammerbacher agrees that Facebook could sell its data science and points to its currently free Insights service for advertisers and website owners, which shows how their content is being shared on Facebook. That could become much more useful to businesses if Facebook added data obtained when its \u201cLike\u201d button tracks activity all over the Web, or demographic data or information about what people read on the site. There\u2019s precedent for offering such analytics for a fee: at the end of 2011 Google started charging $150,000 annually for a premium version of a service that analyzes a business\u2019s Web traffic.<\/p>\n\n\n\n
Back at Facebook, Marlow isn\u2019t the one who makes decisions about what the company charges for, even if his work will shape them. Whatever happens, he says, the primary goal of his team is to support the well-being of the people who provide Facebook with their data, using it to make the service smarter. Along the way, he says, he and his colleagues will advance humanity\u2019s understanding of itself. That echoes Zuckerberg\u2019s often doubted but seemingly genuine belief that Facebook\u2019s job is to improve how the world communicates. Just don\u2019t ask yet exactly what that will entail. \u201cIt\u2019s hard to predict where we\u2019ll go, because we\u2019re at the very early stages of this science,\u201d says \u00adMarlow. \u201cThe number of potential things that we could ask of Facebook\u2019s data is enormous.\u201d<\/p>\n\n\n\n