Elsewhere

Content, Context, Conduit: It’s Not Who You Know, But Where You Know

The other night I was a participant on TummelVision, and one topic that came up was influence. I digressed and starting talking about betweenness, stating that being connected to people in very different ‘scenes’ is much more important than popularity in influencing people:

Stowe Boyd,  It’s Betweenness That Matters, Not Your Eigenvalue: The Dark Matter Of Influence

The most connected people in a social network — those with the highest number of incoming and outgoing connections — have high eigenvalues. These eigenvalues can be calculated — like Google’s PageRank algorithm — by weighting the value of each connection based on the eigenvalue of the originator.

But this research [ARVIX blog, Best Connected Individuals Are Not the Most Influential Spreaders in Social Networks] suggests that a different way to measure the centrality might be more useful in determining how much throw weight a person actually has. Betweenness is a measure of how short are the chains that connects a person to the totality of the network. Like PageRank, betweenness is recursive: the people with the highest betweenness are likely to be connected to other people with high betweenness.

it’s not who you know: it’s where you know. It’s where you are situated in the network, and not just in the limited sense of how many immediate contacts you have.

This means people are influential because they are connected to many influential people. But influence doesn’t seem directly linked to how many people you are connected to. It’s a function of being connected to others who have short chains to many other people with high betweenness. Or, looked at differently, betweenness is a measure of how many social circles, or social scenes, a person is connected to.

So, it’s not who you know: it’s where you know. It’s where you are situated in the network, and not just in the limited sense of how many immediate contacts you have

I think this also is closely related to the notion of curation, which is being discussed a great deal these days, including the recent Business Insider Ignition conference:

Jared Keller, Who Do You Want Telling You What to Read?

I listened to John Borthwick of startup incubator Betaworks, Garrett Camp of discovery engine StumbleUpon, Patrick Keane of Associated Content, and Mark Josephson of the hyperlocal Oustide.in discuss the merits of algorithmic and crowdsourced modes of navigating the news. They’re all like me: they primarily discover content through a carefully curated Twitter feed, an RSS reader, or some other social news service.

So which is better? It’s usually a mix of the three. “Technology, math and algorithms are being used to refine and understand how people filter what they are looking at and how they read,” Borthwick said. “But mainly people read the voice of other people. There are new tools for getting there, so content production is being pushed into the pale, but most of these tools when they are used well are used to surface and filter, not compose.”

"In social media, everyone should be a content creator and curator," Camp added. "StumbleUpon is trying to blend both worlds by asking for human input on thumbing stories up and down."

In this sense, algorithms aren’t replacing editors or individual voices, but are used out of necessity: as the cost of creating content continues to drop, the sheer amount of content available to consumers has exploded. Algorithms are just there to lead the way. And sometimes those algorithms help us find content that, while not produced professonally, has an incredible amount of value.

So it’s not the content, which is the readage. Nor the context, as delivered by better metadata. And it’s not even the act of picking what is best, and passing it along, which is what most people mean by curation. What is really core are the actions taken to increase betweenness, by adding conduits to others who are well-connected and dropping ones that are less well-connected.

I am not sure how ‘carefully curated’ these folks’ twitter streams are, actually, but leave that aside. It is obvious that there is a very fast movement away from search and RSS, and toward Twitter as a source of readage for the world of media and mediaheads.

Instead of considering what we are doing as filtering, or curating, we should think about tinkering with our connections as a way to position ourselves in the network to maximize certain characteristics for the nodes we occupy.

Take betweenness, for example. I try to follow people who are connected to very well-connected people, where ‘well-connected’ does not mean popular, per se, but instead means connected to many people in different walks of life, different countries, different jobs.

The outcome of this tinkering with my connections is that I increase my betweenness: I shorten the number of links than connect me to the entire network, and the world.

Looking at it another way, I am also increasing my utility to those that follow me by increasing my betweenness: they are more likely to find unique insights or innovative ideas by following me, since I bridge many social scenes.

It’s a virtuous cycle: by adjusting my position in the network — by following and unfollowing — I improve the diversity and quality of readage I see, and by passing along the best of what comes along, my followers are better off. My actions improve their respective positions in the network too. And those of their followers, and so on. I am actually improving the entire network, by better positioning myself.

So it’s not the content, which is the readage. Nor the context, as delivered by better metadata. And it’s not even the act of picking what is best, and passing it along, which is what most people mean by curation. What is really core are the actions taken to increase betweenness, by adding conduits to others who are well-connected and dropping ones that are less well-connected.

And, no, there aren’t any algorithmic solutions out there for this. It would be handy if Twitter or Klout would offer up a betweenness value for a given user, or offer up some recommended connections based on the principle of positioning myself better in the network, not just because of topical relevance, or popularity. But they don’t.

Could you get on that guys?

Blog comments powered by Disqus

Notes

  1. messel reblogged this from stoweboyd
  2. stoweboyd posted this
Related Posts Plugin for WordPress, Blogger...