The Complications of Influence

I've been taking some time over the Thanksgiving break to catch up on my Instapaper queue, so I'll probably be posting links to some older articles over the next few days. The first comes from a SocialFlow blog post about how the Osama Bin Laden death news spread across Twitter. While the particulars are interesting, I especially liked the points they made about how impossible it would have been to predict the players actually responsible for spreading the message. The post explain, "Before May 1st, not even the smartest of machine learning algorithms could have predicted Keith Urbahn’s online relevancy score, or his potential to spark an incredibly viral information flow." They then conclude with a deeper message for how we think about social influence that I completely agree with:

As we build out digital social spaces, we must not get derailed by metrics of status affordances that have taken center stage. Just because we have easily accessible data at our fingertips doesn’t mean that we have the capacity to model and place a value tag on human behavior. Followers, friends or likes represent an aspect of our digital status, but are only a partial representation of our general propensity to be influential. Keith Urbahn wasn’t the first to speculate Bin Laden’s death, but he was the one who gained the most trust from the network. And with that, the perfect situation unfolded, where timing, the right social-professional networked audience, along with a critically relevant piece of information led to an explosion of public affirmation of his trustworthiness.