Gravity7: Social Interaction Design SxD By Adrian Chan

I’m back to ranting today, so I’ll keep this one as brief as possible. I was going to write about something completely different, until I took a peek at a tweet from friend and SNCR colleague Tom Foremski on influence. The fact that I clicked through proves to me that Tom has some influence. The fact that I retweeted his tweet confirms, according to the research he blogged about, that he has influence. If you read this and tweet about it, then I’ll have influence too.

Isn’t that simple and wonderful?

This influence thing gets under my skin. Twitter is a communications platform. For every tweet there’s effectively a speaker and listeners. Because it’s mediated, asynchronous, and because it’s twitter, the message isn’t always heard. Sometimes it’s heard much later. Sometimes, heard only because a number of folks say the same thing at roughly the same time. Sometimes it’s heard by those in the adjacent room, because somebody took the message down the hallway. Sometimes it’s heard because it’s picked up by media coverage.

In all cases, however, there is a speaker and a listener. So why then do so many of the industries that invest in social media insist on audience size (followers) as a means of measuring audience reach? And why is the more sophisitcated approach — influence, not absolute follower count — so often just a repackaging of the subscription/circulation model? Sure, retweets count, but when people talk and others listen, it’s never as simple as the measurement of what’s been quoted and cited.

When I did a small project with Klout on their influencer categories, we were able to go from four to sixteen. And we left some out! We found users who relate to twitter as if it were just a publishing medium. We found those who relate to their friends, and for whom tweeting is a kind of open, slow, chat.

We found users invested in their reputations and image as either social figures, experts, critics, and more. We found those for whom there was a strong degree of connecting peers and others socially — for whom twitter really is a social scene — and those for whom it was more a mini-Me-dium, capable of producing both the image of celebrity and its associated social capital.

in all cases we could have done more with more data, but it was clear even with what we had that users adopt very different habits of @naming, following, reciprocating, re-tweeting, listing, and more. All make sense from the user’s relationship to twitter. But none would provide the simplistic and reductionist formula of follower = popular, or influence = retweetability.

Those are measures, well, measures of measurements. They’re numbers and have as much meaning as they can reliably represent. Which, IMHO, is relatively little and possibly misleading. It’s easy to get followers. It’s also easy to get retweeted. There are bots and networks on twitter engaged in gaming both. But where’s the value, to a brand, in paying attention to those kinds of “influence” metrics?

If traffic slows on the freeway as rubber-necking turns its attention to a roadside accident, is that influence? Or how about the guy leading a small fleet of cops on a high-speed chase while eyewitness news feeds the whole thing back to the network? Is there influence in the crowd that forms in passing? A mob that runs riot down the street? How about the influence of a stadium crowd? And if the concert is streaming live, who’s influential — the band, the crowd in attendance, the band’s followers online, their retweeters, or ustream?

I just think the approach is over-simplified and a bit remedial. The fact of a crowd, eg audience number, tells us nothing about the reason for the gathering. It might be transient and owe all to crowd psychology. Or it might be the single most riveting event in human history. Say a moon landing or a world cup.

Or take the quote and citation that makes the rounds as a headline or a newsbite. It may indeed be of some import and significance. But it may also just be a bit of news. Fact is that from the numbers, traffic flow, distribution, rise and decay of this one retweet or citation, we don’t know.

How can a quantitative measure of audience size tell us about popularity, or a retweet count tell us about influence?

What is measured about audience in gross numerical terms; or sifted out of traffic as quotations, provides no insight into the intent or meaning created by speakers, or the consensus and agreement reached with listeners.

Perhaps some marketers just really need to segment audiences. Perhaps their reporting requires numbers and quantitive trends. Then they’ll get just that. But those metrics will say nothing about the motives and intentions of twitter users; will say naught of the reasons those users try to move their followers and readers (trust? expertise? admiration? pure celebrity? insight? newsworthiness?). And will say little about why their followers are moved to read, follow, or retweet.

In any communication system, “influence” is a relation, between speaker and listener. The speaker doesn’t have influence because she speaks or for what she says. It is only the listener’s attention and acceptance or rejection of what she says that results in what we call influence. It is always a coupled, doubly-dependent, reciprocating and mutually-influential system. And you cannot measure the value created and paid for with mutually sustained attention (yes, even twitter is mutually-sustained attention. It’s just really episodic and discontinuous.)

It takes two to tango. Or you can drop your partner and count the people in the room. Call it a hit.

I strayed far from the report in question, but here’s the conclusion, as cited by Tom:

“Given the mushrooming popularity of Social Media, vast efforts are devoted by individuals, governments and enterprises to getting attention to their ideas, policies, products,and commentary through social networks.

But the very large scale of the networks underlying Social Media makes it hard for any of these topics to get enough attention in order to rise to the most trending ones.

Given this constraint, there has been a natural shift on the part of the content generators towards targeting those individuals that are perceived as influential because of their large number of followers.

This study shows that the correlation between popularity and influence is weaker than it might be expected.

This is a reflection of the fact that for information to prop-agate in a network, individuals need to forward it to the other members, thus having to actively engage rather than passively read it and cease to act on it.

Moreover, since our measure of influence is not specific to Twitter it is applicable to many other social networks.

This opens the possibility of discovering influential individuals within a network which can on average have a further reach than others in the same medium regardless of their popularity.”

from Influence and Passivity in Social Media – HP Labs Research