Almost nothing is “uniquely American,” except for Americans’ overuse of that phrase. But the idea of likability comes close to being an American obsession. Other cultures demand that their leaders, thinkers, and literary heroes live up to specific ideals. We simply expect that ours will please a hypothetical sampling of the media-viewing public. We’ll tolerate someone’s moral complexity and tragic flaws, so long as he kinda-sorta seems like a good guy.
What makes someone likable is hard to qualify. Perhaps that’s why we’ve tried so hard to quantify it. Back in 1963, Jack Landis of Marketing Evaluations Inc., devised the Q Score: a simple measure of someone’s public favorability, divided by his public awareness. Based on surveys, and vulnerable to selection biases, the Q Score was imperfect. But it survived for decades, because it addressed market demand: demand to know who was likable, to what degree, and under what circumstances. Marketers could convert that knowledge into influence, and influence into sales.
Klout once aspired to be the Q Score of the Internet: a way of tracking reach and influence across Facebook, Twitter, LinkedIn, and other social media. Its algorithm has always been a black box. But the company moved beyond the vanity metrics of social media—things like number of friends or followers—and into deeper indicators of engagement, like retweets. By doing so, Klout tried to become the world’s first and most reliable standard of measuring social influence.
It never quite got there. First there were some embarrassing missteps, like the time Klout Scores indicated Justin Bieber was more influential than the Dalai Lama and the president of the United States. (Klout’s response: Well, maybe he is.) Over time, the ridicule gave way to fretting and groaning—fear, for instance, that the same algorithm bestowing political and spiritual primacy upon Justin Bieber would be used to evaluate job candidates. At that point, pretty much anyone who didn’t have a three-album deal with Island Records was rooting for Klout’s failure.
Haters got their wish: In March, Klout was sold off to Lithium Technologies. A reported $200 million acquisition is no crash landing. But as a serious Internet standard, the Klout Score is spent. Klout Scores rarely showed up in the job-application process, let alone became a standard. Klout has no bearing on, and receives little mention in, any of our society’s great popularity contests: elections, celebrity feuds, Twitter memes, or 24-hour news cycles. We’re not reading, in the ad-industry trade papers, about multimillion-dollar Klout campaigns. As measured by Google Trends, Klout reached the peak of its clout around May of 2012. And now everyone’s rushing in to claim it was inevitable—that Klout never had a chance in the first place.
That’s not exactly true. Klout failed to achieve its original goals, but not because those goals were flawed. As advertisers pour billions of dollars into social channels, they (and their agencies) will demand more measurability and accountability of those channels. Accountability is a good thing, and not just for brand marketers. It would act as a strong disincentive toward gaming social systems—for example, collecting thousands of followers or pumping out clichéd status updates to farm Facebook likes.
Klout wanted to force accountability on the social world. That’s a legitimate premise. But in execution, Klout got everything backward. Its system created a selection pressure for frivolity at the expense of truth.
First, it encouraged users to link disparate sources, like Instagram and LinkedIn, to the same Klout Score. This was a mistake because people compartmentalize their personalities, their friends lists, and even their lives, by the social networks they use. Mashing everything and everyone together—colleagues and drinking buddies, parents and bosses—causes those users to water themselves down. It forces them to select the lowest common denominator of their personalities, twisting and straining to appease the aggregate social circle.
Klout might respond that it doesn’t intermingle the data from Facebook with the data from LinkedIn, and accordingly, users don’t have to worry about the aggregate mix. Each network’s data are independent sets of variables in the Klout Score equation. But in practice, people don’t think that way. Throughout Klout’s history, nobody referred to a “Klout Facebook Score” or a “Klout LinkedIn Score,” so much as the combined and universal Klout Score. It’s easy to imagine that people who take their Klout Score seriously could become acutely aware of the aggregation. That awareness infects people’s behaviors on each channel, leading to a version of the observer effect.
And if people believe those scores are being judged, especially in life- or career-affecting ways, they have every incentive to game the scores. They are goaded into behaving artificially on social networks: sharing safe Like-bait, and holding back anything they deem quirky, eccentric, or controversial. Anyone who doesn’t want to be an “influencer” comes under intense pressure to be, especially as “influence” becomes a measure of self-worth. The result: a lot more people trying to pass around the same articles, memes, and themes. A lot more homogeneity. A lot more noise, masquerading as signal. A self-defeating search for quality in an ocean of quantity.
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