Tag Archives: social-networking

How Trends Actually Spread; or, Six Degrees but No Connectors

The small sample size of Stanley Milgram’s small world experiment means that the theory of ‘six degrees of separation’ and the conclusion drawn from it–primarily, the Influential’s theory popularised by Malcolm Gladwell in The Tipping Point–could be deeply flawed. That was the starting point for Duncan Watts‘ research that led him to say “the Tipping Point is toast”.

So to research how ideas and trends spread virally, Watts (who is author of Everything is Obvious, principal research scientist at Yahoo! Research (he directs their Human Social Dynamics group), and founding director of Columbia University’s Collective Dynamics Group) ran large-scale reproductions of the small world experiment and hundreds of computer simulations that brought forward two conclusions: the six degrees of separation theory is correct, but there is no evidence for super-connected ‘trend gatekeepers’ (such as Gladwell’s ‘Connectors’):

But Watts, for one, didn’t think the gatekeeper model was true. It certainly didn’t match what he’d found studying networks. So he decided to test it in the real world by remounting the Milgram experiment on a massive scale. In 2001, Watts used a Web site to recruit about 61,000 people, then asked them to ferry messages to 18 targets worldwide. Sure enough, he found that Milgram was right: The average length of the chain was roughly six links. But when he examined these pathways, he found that “hubs”–highly connected people–weren’t crucial. Sure, they existed. But only 5% of the email messages passed through one of these superconnectors. The rest of the messages moved through society in much more democratic paths, zipping from one weakly connected individual to another, until they arrived at the target. […]

[His computer simulation] 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.

I can’t help but find it somewhat ironic that, written almost four years ago, this argument hasn’t really gained much traction and Gladwell’s ideas are still discussed ad nauseam.

Inventive Ways to Control Trolls

To keep the peace on the ever-expanding Stack Exchange Network of online communities, owners Joel Spolsky and Jeff Atwood introduced the timed suspension of disruptive users’ accounts. Over time the transparency of the timed suspension process proved to be occasionally inefficient when discussions arose regarding the merits of certain suspensions. This led the administrators of the communities to investigate other ways of moderating problematic users.

What they found were three fantastically devious secret ways to effectively control trolls and other abusive users on online communities: the hellban, slowban, and errorban:

A hellbanned user is invisible to all other users, but crucially, not himself. From their perspective, they are participating normally in the community but nobody ever responds to them. They can no longer disrupt the community because they are effectively a ghost. It’s a clever way of enforcing the “don’t feed the troll” rule in the community. When nothing they post ever gets a response, a hellbanned user is likely to get bored or frustrated and leave. I believe it, too; if I learned anything from reading The Great Brain as a child, it’s that the silent treatment is the cruelest punishment of them all. […]

(There is one additional form of hellbanning that I feel compelled to mention because it is particularly cruel – when hellbanned users can see only themselves and other hellbanned users. Brrr. I’m pretty sure Dante wrote a chapter about that, somewhere.)

A slowbanned user has delays forcibly introduced into every page they visit. From their perspective, your site has just gotten terribly, horribly slow. And stays that way. They can hardly disrupt the community when they’re struggling to get web pages to load. There’s also science behind this one, because per research from Google and Amazon, every page load delay directly reduces participation. Get slow enough, for long enough, and a slowbanned user is likely to seek out greener and speedier pastures elsewhere on the internet.

An errorbanned user has errors inserted at random into pages they visit. You might consider this a more severe extension of slowbanning – instead of pages loading slowly, they might not load at all, return cryptic HTTP errors, return the wrong page altogether, fail to load key dependencies like JavaScript and images and CSS, and so forth. I’m sure your devious little brains can imagine dozens of ways things could go “wrong” for an errorbanned user. This one is a bit more esoteric, but it isn’t theoretical; an existing implementation exists in the form of the Drupal Misery module.

A Summary of Happiness Research

David Brooks brings ‘happiness research’ back to the wider public’s attention with a succinct summary of research into what does and does not make us happy:

Would you exchange a tremendous professional triumph for a severe personal blow? […]

If you had to take more than three seconds to think about this question, you are absolutely crazy. Marital happiness is far more important than anything else in determining personal well-being. If you have a successful marriage, it doesn’t matter how many professional setbacks you endure, you will be reasonably happy. If you have an unsuccessful marriage, it doesn’t matter how many career triumphs you record, you will remain significantly unfulfilled.

Brooks goes on to look at the confusing correlations between happiness and wealth before discussing the wider “correspondence between personal relationships and happiness”:

The daily activities most associated with happiness are sex, socializing after work and having dinner with others. The daily activity most injurious to happiness is commuting. According to one study, joining a group that meets even just once a month produces the same happiness gain as doubling your income. According to another, being married produces a psychic gain equivalent to more than $100,000 a year.

If you want to find a good place to live, just ask people if they trust their neighbors. Levels of social trust vary enormously, but countries with high social trust have happier people, better health, more efficient government, more economic growth, and less fear of crime (regardless of whether actual crime rates are increasing or decreasing).

via Fred Wilson

I discussed the ‘commuters paradox’ last year, noting that “a person with a one-hour commute has to earn 40 percent more money to be as satisfied with life as someone who walks to the office”.

Social Networks and Their Far-Reaching Influence

In a short and balanced review of Connected–“a scientific look at the ties that bind us together”–we are treated to some interesting findings on social networks and their myriad external effects–including how far these effects ‘travel’ through said networks.

Controlling for environmental factors and the tendency of birds of a feather to flock together […] Christakis and Fowler found that we really do emulate those we care about, whether we mean to or not. Being connected to a happy person, for instance, makes you 15 percent more likely to be happy yourself. “And the spread of happiness doesn’t stop there,” they note. It radiates out for three degrees of separation, so that, say, your sister’s best friend’s husband’s mood exerts a greater influence on your personal happiness than an extra $10,000 in income would. If he gains 50 pounds, it will be that much harder for you to stay slim, as the frame of reference for what’s “normal” changes through your network. Or, on the positive side, if he quits smoking, your chances of kicking the habit improve, too, even if you’ve never met him. […]

Public health workers can more effectively stop the spread of sexually transmitted diseases if they know what kind of network they’re dealing with: a hub and spoke (e.g., a prostitute with many clients) or a more transitive “ring” network where people have few partners, but many of these partners overlap (which could happen at a small high school). On another front, they point out that voting makes little sense for an individual—one vote never decides an election—but is far more rational in a network context. As with happiness and obesity, the decision to vote has repercussions through three degrees of connections. […] Since liberals and conservatives tend to form their own social networks, this means that your decision to vote can increase the likelihood of hundreds of other people voting for the same candidate.

I do wonder if these degrees of separation that exert influence on us fluctuate with the size of each ‘degree’?

Making Applications Viral, Without Spam

Virality isn’t an indispensable feature of all successful applications, but for those where it can be hugely beneficial there are four core principles that help the virality of an application, says Daniel Tanner:

  • Invitation should be a core process, that is essential to using the application – this will maximise the chances that your users do invite new users.
  • Keep pulling people back in, rather than letting them forget you after the initial invitation, and make this “reminder” process also be central to the use of the application.
  • Be useful even to the lone user, because that lone user is the source of all your other users.
  • Remove artificial invitation limits, to recognise the reality that most invitations come from a few very active users, and help those users spread the word.

Tenner also notes–in passing–the concept of the viral loop. Andrew Chen’s take on the loop is the best I’ve read on the topic.