Tripping up the Tipping Point

Fascinating piece in Fast Company, talking about how memes are spread in social networks. Essentially its a Fast Fisk using research by one Duncan Watts, of Malcolm Gladwell's Tipping Point (and by extension those that adhere to the view that some people are more influential than others:

"Oh, God," he groans when the subject comes up. "Not them." The Hush Puppies in question are the ones that kick off The Tipping Point, Malcolm Gladwell's best-seller about how trends work. As Gladwell tells it, the fuzzy footwear was a dying brand by late 1994--until a few New York hipsters brought it back from the brink. Other fashionistas followed suit, whereupon the cool kids copied them, the less-cool kids copied them, and so on, until, voilà! Within two years, sales of Hush Puppies had exploded by a stunning 5,000%, without a penny spent on advertising. All because, as Gladwell puts it, a tiny number of superinfluential types ("Twenty? Fifty? One hundred--at the most?")

These tastemakers, Gladwell concluded, are the spark behind any successful trend. "What we are really saying," he writes, "is that in a given process or system, some people matter more than others."

Duncan Watts's research tells advertising execs precisely what they don't want to hear: All their clever (and lucrative!) targeted viral campaigning may ultimately be less effective than good old mass marketing.

In essence, this is laying out some research that Watts has performed that apparently refutes much of the Tipping Point work. There is some very interesting output:

He has analyzed email patterns and found that highly connected people are not, in fact, crucial social hubs. He has written computer models of rumor spreading and found that your average slob is just as likely as a well-connected person to start a huge new trend. And last year, Watts demonstrated that even the breakout success of a hot new pop band might be nearly random. Any attempt to engineer success through Influentials, he argues, is almost certainly doomed to failure.

I say it apparently refutes Gladwell et al - and the Fast Company guys do a good job of setting up an either/or storyline, as is their wont. However, if you read the article closely (and if you've ever actually read Gladwell's book - or more crucially, some of the academic work behind some of those conclusions) you'll see that in fact the body of knowledge that has gone before has not quite been composed by a bunch of idiots. In fact:

Gladwell's book laid out many other factors that can "tip" a trend. He described other influential types: Mavens, who love to collect information and help others make decisions, and suave Salesmen of ideas. In order to spread, an idea or product had to be "sticky," and appear in a fertile social context. But as The Tipping Point climbed the charts, marketers fixated on Gladwell's Law of the Few, his suggestion that rare, highly connected people shape the world. For anyone involved in pitchmanship, it was an electrifying notion, one that took a highly complex phenomenon--the spread of memes through society--and made it simple. Reach the gatekeepers, and you reach the world.

In other words the PR and Social Media chatterati got a superficial end of the stick and ran off with it at full speed, neglecting all the nuances. A fertile field then for a New New Social Marketing Guru to plough

And if that person just happened, over the past three years, to have worked on a new form of advertising he calls "Big Seed marketing" as part of his work at a certain Yahoo, where he is a principal research scientist, (and where he developed the concept with a friend, Jonah Peretti, a veteran of the viral wars), you may just suspect that there is a certain amount of influencing going on here too.....

But I do like the way he's done the work - using an Artificial Life simulation setup to experiment with - because I've been fascinated with simulation and A-Life for decades, and have written quite a few simulations and system dynamic programs in my time. This is fascinating:

He programmed a group of 10,000 people, all governed by a few simple interpersonal rules. Each was able to communicate with anyone nearby. With every contact, each had a small probability of "infecting" another. And each person also paid attention to what was happening around him: If lots of other people were adopting a trend, he would be more likely to join, and vice versa. The "people" in the virtual society had varying amounts of sociability--some were more connected than others. Watts designated the top 10% most-connected as Influentials; they could affect four times as many people as the average Joe. In essence, it was a virtual society run--in a very crude fashion--according to the rules laid out by thinkers like Gladwell and Keller.

Watts set the test in motion by randomly picking one person as a trendsetter, then sat back to see if the trend would spread. He did so thousands of times in a row.

The results were deeply counterintuitive. The experiment did produce several hundred societywide infections. But in the large majority of cases, the cascade began with an average Joe (although in cases where an Influential touched off the trend, it spread much further). To stack the deck in favor of Influentials, Watts changed the simulation, making them 10 times more connected. Now they could infect 40 times more people than the average citizen (and again, when they kicked off a cascade, it was substantially larger). But the rank-and-file citizen was still far more likely to start a contagion.

Though actually, its not counterintuitive at all - anyone who has studied some of the literature on the spread of diseases, memes etc would have expected results something like this - the academic literature is full of this sort of work going back 2 decades at least. And the reason why is actually given later:

Why didn't the Influentials wield more power? With 40 times the reach of a normal person, why couldn't they kick-start a trend every time? Watts believes this is because a trend's success depends not on the person who starts it, but on how susceptible the society is overall to the trend--not how persuasive the early adopter is, but whether everyone else is easily persuaded. And in fact, when Watts tweaked his model to increase everyone's odds of being infected, the number of trends skyrocketed.

Memeticists and A-Lifers have built memetic and genetic algorithm based models for many years now that show time and again that its the strength of the meme - its ability to hook - that really drives the spread rate. Well connected nodes just spread it further, faster. Disease researchers are well aware that its the way a disease is transmitted, not just the connectedness, that spreads it. But all research has shown that soem nodes are more connected, and if you hit that node then the meme/disease/whatever gets a big Mo. And - guess what - it has been shown in study after study that some individuals in groups are more influential / dominant / (insert your un-PC term here) than others, and people - (shock horror) - follow them, and even emulate their behaviour.

And the problem of course with simulation models is just that - they are imperfect models of the world. They do give amazing insights however, but I do feel that in this particular case there has been a certain amount of pimping the "known unknowns" in the body of work

In fact, there is at the end a (sort of) coming together of the parties at the party if you read on.

Watts does agree that some people are more instrumental than others. He simply doesn't think it's possible to will a trend into existence by recruiting highly social people. The network effects in society, he argues, are too complex--too weird and unpredictable--to work that way. If it were just a matter of tipping the crucial first adopters, why can't most companies do it reliably?

and...

For his part, Gladwell is diplomatic. "Duncan Watts is exceedingly clever, and I've learned a great deal from his research," he emailed me. "In the end, though, I suppose that I feel the same ways about his insights as I do about Steve Levitt's disagreements with me over the causes of the decline in violent crime in the 1990s. I think that all books like The Tipping Point or articles by academics can ever do is uncover a little piece of the bigger picture, and one day--when we put all those pieces together--maybe we'll have a shot at the truth."

The problem of course is that the background body of work is nuanced, dispersed across disciplines, quite dense, potentially contradictory - as not all vectors are always teased out - and thus not at all attractive to the chatterati, who:

cling to their belief in Influentials partly because they're lazy. They love the idea of needing to reach only a small group of people to "tip" a product.....Plus, it strokes their egos: "Think about it. You're saying, 'I am in control--I am the biggest influencer, because I am going to influence the influencers!' It's an arrogance that only the corporate world could enjoy."

Quite so. And no doubt the chatterati will now go racing off saying everything is random, as this is the New New Meme, and its a sticky one too as it allows lots of Small People to wallow in the delusion that We Are all Equal After All. But hold on there before you go penduluming off in that thar other direction! Be honest with yourself - why do some people have 5,000 followers on Twitter or Facebook and others have few? Why do the Big Nodes get all the Link Lurve? Why are some kids on the playground time and and again bossing the others around? Recall teh 1:9:90 ratio on nearly all Social Nets! The actual background work shows that there is far a more complex interaction going on between the Zeitgeist and the Great Man theories. The truth is somewhere in between these (artificial) poles.

And that term "complex" implies to me that the one thing that Watts hasn't quite got (assuming Fast Company summed him up correctly of course) is summed up here:

Actually, if you believe Watts, the world isn't just complex--it's practically anarchic. In 2006, he performed another experiment that chilled the blood of trendologists. Trends, it suggested, aren't merely hard to predict and engineer--they occur essentially at random.

I doubt its random - essentially these are complex interactive systems, and they are usually demonstrably chaotic, not random - an altogether different thing.

Update - coverage of this in Ars Technica, with a corollary - it ain't the influencers, its the influenced that are responsible for all this influenza.