A Social-Media Decoder

A Social-Media Decoder

New technology deciphers— and empowers—the millions who talk back to their televisions through the Web.

 

 Deb Roy

From his 24th-floor corner office in midtown Manhattan, the veteran CBS research chief David Poltrack can gaze southward down the Avenue of the Americas, its sidewalks teeming. For more than four decades, it has been his job to measure people's television habits, preferences, and reactions. In large part, this has meant following the viewing habits of Nielsen panels of TV viewers and parsing the results of network surveys on their opinions. On a late September afternoon, with fall premieres under way, his desk was strewn with color-coded opinions from 3,000 Americans who had wandered into CBS's Las Vegas research outpost, Television City, at the MGM Grand Hotel and Casino, and agreed to fill out TV surveys for the chance to win a 3-D home entertainment system.

Power shift: Deb Roy, CEO of Bluefin Labs, says social media have changed the relationship between media consumers and producers. Credit: Ian Allen

 

But now he's also dealing with a growing force: the masses talking back through social media. Of the approximately 300 million public comments made online worldwide every day—about two-thirds of them on Twitter—some 10 million, on average, are related to television (though daily numbers vary quite widely). "¿Que sera two and a half men si[n] Charlie?" one viewer recently tweeted, alluding to the replacement of Charlie Sheen by Ashton Kutcher on the CBS sitcom. "The beginning of Person Of Interest is like Jack&Ben all over again," remarked another. (A couple of weeks later, another added: "I assume CBS will keep going with what's been working for them, and replace Andy Rooney with Ashton Kutcher.") TV executives like Poltrack must now grapple with these spontaneous, messy, irreverent remarks.

How to make sense of it all? Poltrack walked into the office of a staff member, John Butler, clutching a report from a startup called Bluefin Labs, a social-media analytics firm that attempts to track comments on shows and ads and discern the commenters' interests and demographics. Some of what it had found seemed surprising. For example, the season premiere of Two and a Half Men had attracted 78,347 comments compared with 82,980 forDancing with the Stars, on ABC, even though the latter show has lower Nielsen ratings and an older audience that's less likely to participate in social media. (It turns out that reality competition shows, by their nature, attract more active audience response.) Poltrack wondered how a little-watched show called Bad Girls Club—on the Oxygen network—had garnered 32,665 comments. "Get Bad Girls Club up there," he said to Butler, motioning to Butler's computer screen. "What are they saying?" Butler scrolled through the raw comment string. "This bitch angie on #Badgirlsclub wear the same damn socks in every episode,"remarked one viewer; "BGC, shower & bed," announced another. It was hard to know what any of it meant.

Overall, the data was raw and, in many cases, ambiguous. But Poltrack came away with some respect for what he was seeing. "As a one-time measurement, we have better ones," he said, referring to CBS's precisely constructed surveys. But whereas the surveys are intermittent, social-media analytics can provide "a continuous monitor of conversation about a program, episode by episode," he said. "And that is something we can't replicate." What's more, the quantity of commentary is increasing all the time, making it more important as an object of study and as a force network executives would like to harness. As Poltrack explained, real-world and online chatter—the "exponential movement of a conversation through the population"—drives the success or failure of TV shows and, in turn, the allocation of $72 billion in U.S. television ad spending.

Six hundred miles to the west, a similar assessment was under way at the Cincinnati headquarters of Procter & Gamble, the world's largest advertiser (its brands include Tide, Gillette, Bounty, Pringles, and Duracell). Each year the company spends $5 billion on media ads—the bulk of them on TV—and another $5 billion on in-store advertising worldwide. While Procter & Gamble carefully vets ads with consumers before airing them, it has never known whether the same viewers would respond differently to an ad depending on what show surrounded it.

Craig Wynett, the company's chief learning officer, says Bluefin Labs is teasing out nuances in the way context affects the extent to which an ad generates buzz. One specific product ad (he wouldn't say which) was placed on two shows with similar demographics and ratings. One show produced eight times more social-media response than the other. Nobody knows why, but that's what happened. "Historically, we have held context as a constant. Well, surprise! In the real world, context plays a fundamental role," he says.

Bluefin Labs is one of a growing number of analytics companies parsing the meaning of comments in social media. And its CEO, Deb Roy, believes they are capturing a fundamental change in the relationship between creators and consumers of mass media. "What I have learned by hanging out with TV executives, talent agencies, and creative types is that the assumption is built into their organizations' DNA that this is a one-way dialogue," he says. "Audience members speaking through social media is effectively a shift in power."

In some ways, a two-way conversation has begun. And in future years a TV network could, in theory, continue the conversation by revising its promotions to emphasize characters that have caught on with audiences—or even by revising plot lines midway through a season. Advertisers, meanwhile, could swap out ads—or place them differently—on the basis of the social-media response they get. (Something like this already happens with online ads; increasingly, algorithms use real-time metrics like page views and content changes to guide placement decisions.) In the political realm, campaigns could rapidly determine, among other things, which messages animate people. And early feedback from the first adopters of analytics—network executives and advertisers—could provide clues to wider potential impacts. Wynett says he doesn't know if the people who commented on his advertisement bought the product or "if the message spread until every man, woman, and child heard it." Still, he says, "It's early days, but it shows promise."

MINING SOCIAL SENTIMENT

Analyses of online comments are already influencing corporate, financial, and governmental behavior. Certain companies, Comcast among them, keep an ear open for outbursts of anger to help them detect and respond to service outages and product problems. A London hedge fund, Derwent Capital, makes trades based on the financial calm or anxiety it gleans, in part, from social-media data. And while recent events have suggested that revolutionaries can use social media to help them overthrow some authoritarian regimes (see "Streetbook," September/October 2011), China has learned to manage citizen outrage through measured responses to specific online complaints about matters such as police corruption (see "China's Internet Paradox," May/June 2010). 

Playing ball: As a doctoral candidate, Michael Fleischman used televised Red Sox games to teach computers to recognize home runs and other plays. Now the company he cofounded, Bluefin Labs, analyzes social media to decipher mass reactions to TV shows and ads viewed in the United States. In its offices, a screen (top) displays the number of comments searched, minutes of TV ingested, and connections found. Credit: Ian Allen

For marketing purposes, it has become de rigueur for companies to set up Facebook pages and send out tweets, and to keep a watchful eye on the bubbling up of blogged anger. This is true of television networks as well as other companies. For example, Discovery Communications, which runs channels including the Discovery Channel, TLC, and Animal Planet, maintains 75 Facebook pages with 45 million fans, and keeps 23 Twitter accounts crackling with reminders like "Mythbusters starts in 5 minutes!" "It's all that beautiful viral effect of social media to get people to watch our shows," says Gayle Weiswasser, Discovery's vice president of social-media communications, "and we aren't the only ones who do it."

To tap the other side of the conversation—the unscripted response of consumers with social-media accounts—companies like Radian6 (now owned by Salesforce), General Sentiment, Sysomos, Converseon, and Trendrr track social-media sentiment and volume on a range of topics. Of course, even the best filtering efforts don't eliminate all spam. And it's not always clear what prompted a post, how a slang-filled tweet should be interpreted, or how to identify the author's demographics. Yet it is "critically important" for businesses to make sense of all this, says Radha Subramanyam, senior vice president of media and advertising insights and analytics at Nielsen: "This is the world's largest focus group, the world's largest town hall. Companies that figure this out will thrive in the next 10 to 15 years. Companies that don't will fail."

It's especially important for TV networks and advertisers. Nielsen says that Americans, on average, spend 20 percent of their day watching TV, and many simultaneously peck away at laptops or mobile devices. Sites like Miso and GetGlue encourage people to discuss favorite shows with friends and other fans. Evidence is emerging that social-media buzz has some relationship to ratings: NM Incite, a Nielsen-McKinsey joint venture, found that among people aged 18 to 34, a 9 percent increase in such chatter in the weeks before a show's premiere correlated to a 1 percent ratings increase.

Recognizing these kinds of connections, sentiment-analysis firms including Trendrr.tv (part of Trendrr) and Socialguide specifically track social response to television content. But Bluefin is unique in also tracking most of what is on TV—including the ads—to draw specific relationships between televised stimulus and social-media response. "What Bluefin is doing is technically impressive," says Duane Varan, chief research officer at the Disney Media and Advertising Lab in Austin, Texas. Already, it's becoming possible to measure TV viewership directly through cable boxes rather than through samples such as Nielsen panels, he says, and "Bluefin is doing a similar thing with this universe of public social-media discourse." 

THE NFL AND SOCIAL TV

Bluefin Labs' headquarters occupy a one-story 19th-century factory that once made hoses, next to a boutique movie theater in the Kendall Square area of Cambridge, Massachusetts. Lego blocks strewn on café tables busy the fingers of visitors or employees at informal meetings. Roy, the cofounder and CEO, sits at one of an open cluster of desks in close quarters with nearly 40 employees, most of them engineers with experience in fields like artificial intelligence, search, and video analysis. A poster showing the "bloodline" of the advertising industry is pinned on a worn wooden post to his right.

Roy, who is 42, is a Winnipeg-born computer and cognitive scientist who until 2008 had spent his entire career in academia, first at the University of Waterloo and then at MIT and its Media Lab, where he became head of a research group called Cognitive Machines. Among other things, his group concerned itself with problems such as how to teach English to robots. In 2005 he launched the ambitiously named "Human Speechome Project" to document how children learn language. Before his son was born, he equipped his home with 11 video cameras and 14 microphones. Then the proud papa recorded (almost) everything that happened in the house to figure out how different adult interactions—as well as activities and objects in different locations of the house—affected the boy's speech development. In 2008, after collecting 300 gigabytes of data every day, Roy stopped. Then he and his graduate students performed feats like charting his son's gradual mastery of the word "water." (A presentation of this process was the hit of the 2011 TED conference and has spread virally throughout the Internet.)

 

 

Posted in: Web