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Simulation "proves" Gladwell wrong

They looked at that information spread in several ways, comparing via computer simulation how information moved throughout the networks when it came solely through word-of-mouth within a network ("bottom up"), when it came solely through external advertising or public information ("top down") and when it came through varying bottom-up and top-down combinations. What they discovered refutes Gladwell's concept that network position is always paramount. They found that in instances where there is even a small amount of advertising -- even when it is just a quarter of a percent as strong as word-of-mouth -- there's virtually no difference between the influence of the person at the center of a network and those further out on the string.

Confessions of an Instagram Influencer - Bloomberg

That night, I signed up for a service recommended to me by Socialyte called Instagress. It’s one of several bots that, for a fee, will take the hard work out of attracting followers on Instagram. For $10 every 30 days, Instagress would zip around the service on my behalf, liking and commenting on any post that contained hashtags I specified. (I also provided the bot a list of hashtags to avoid, to minimize the chances I would like pornography or spam.) I also wrote several dozen canned comments—including “Wow!” “Pretty awesome,” “This is everything,” and, naturally, “[Clapping Hands emoji]”—which the bot deployed more or less at random. In a typical day, I (or “I”) would leave 900 likes and 240 comments. By the end of the month, I liked 28,503 posts and commented 7,171 times.

Clustered Networks Spread Behavior Change Faster | WIRED

To do the experiment, he created an internet-based health community and invited people already participating in other online health forums to join. Over 1,500 people signed up to participate, and they were placed anonymously in one of two different kinds of networks: a random network with many distant ties (above left), or a clustered network with many overlapping connections (above right). Users in both networks had the same number of assigned “health buddies.” They couldn’t contact their buddies directly, but they could see how their buddies rated content on the site, and could receive e-mails informing them of their buddies activities. […]In the clustered network, 54 percent of the people signed up for the forum, compared to 38 percent in the random network, and almost four times as fast. Not surprisingly, Centola also found the more friends people had that also signed up, the more likely they were to return to the forum to participate.

Clustered Networks Spread Behavior Change Faster | WIRED

In the clustered network, 54 percent of the people signed up for the forum, compared to 38 percent in the random network, and almost four times as fast.
Despite the efforts of companies like Klout and Twitalyzer, the industry that’s appeared around “influence” measurement best resembles the early days of search engine optimization. It’s full of tricks, games, and shady third parties trying to game the system to make a quick buck. Anyone with a few hours to spare can create a Twitter bot that not only appears human, but that, according to the best tools we have right now, is a more influential entity than actual people.