That's right, reaching influentials is not the way to reach the many. Duncan Watts says the emergence of a trend does not depend on influentials. Instead, it depends on the susceptibility of the public to the "virus." Social-network effects are so complex, that trends are basically random. Has The Tipping Point peaked? Clive Thompson says so in the February issue of Fast Company magazine.
I participated in Duncan Watts Small World Columbia research project, and although I'm sure he and I have six degrees of separation, we have not met in person. Yet, I have definitely an affinity with his findings. I have felt many times, even from my own observations of social media patterns and from the years of networking, that it is mostly a matter of luck that decides whose story gets noticed. Remember the old adage: right place and right time?
Steve Rubel Tweeted a link to a new Edelman white paper that can help take a closer look at influence. It's titled -- Distributed Influence: Quantifying the Impact of Social Media. Some of the highlights of the paper are:
- It's becoming increasingly important to figure out who are the people who set the tone for online advice -- those who act as conversation catalysts (could I push it and use the word agent?).
- To that effect, a panel composed by Max Kalehoff of Nielsen Buzzmetrics, the Adverting Research Foundation, and Sarah Petersen of StrategyOne on the measurement side got together with the Edelman team under the watchful eye of industry observers Peter Kim and Charlene Li of Forrester and Dr. Walter Carl of Northeastern University to discuss who are the most trusted people, the ones with the loudest voice. Jeff Jarvis of Buzzmachine and Keith O'Brien of PRWeek joined Rubel as publishers. Good starting group.
- How do you calculate an individual's online influence? The Social Media Index was the catalyst for the discussion. Take a look at the report for scores and measurement. At this point I observed that the index, if so adopted, would seem to indicate that unless you participate in an arbitrary list of networks, including Facebook (which I endeavor to avoid), Flickr (another I haven't found reason to use), and Digg, your total score will be lower. Will it be? I think there are more balanced ways of measuring online influence. More on this in another post.
- A definition of influence that also recognizes the role of emotion and external pressure (the crowd factor). We discussed a definition here not long ago. I found the quote from Dr. Carl's article useful to gain some bearings:
“the fact that people also seek to confirm their rightness of how they order/make sense of their world brings communication into contact with community (we define community as our network of personal and social relationships). In this context, to interact within a community of relationships is to engage in interpersonal influence. We are continually seeking to confirm the validity of how we order the environment and, one powerful to confirm our own view of the world is to put our view in communication with others' views, and to have an effect on both others' views and our own.
With social media, people's discourse leaves a digital trail, making it available as a way to infer how people order their environment. In confirming our own views through a process of
communication we often make subtle adaptations to our views. Thus, conversations are everyday negotiations of this sense-making process and to the extent people shift the
discourse, or engage in efforts to reaffirm a certain discourse, we can say influence has occurred. Maintaining or ending a conversations is also a way to engage in influence.”
I will give you an extra couple of minutes to digest the thought of indelible digital trails on your opinions and behaviors.
- There is value in the network and influence can be determined by the meme, which Jeremiah Owyang defined as: an idea or discussion that grows and spreads form individual to individual into a lengthy commentary.
- Definitions of the arc of influence from the perspectives of the influencer and that of the influenced. I disagree with Steve's assertion that influence needs critical mass for action. Instead, it may want critical connection. We are talking about marketing conversation.
- The move to micro communications and a nice formula that has the volume and quality of attention times time over size and quality of audience to represent an individual's online presence.
Admittedly, it's a good start. I am interested in micro communications. The future of social networking may not be one big social graph but instead myriad small communities on the internet to replicate the millions that exist off line.
Much of the paper is focused on people and their individual and network circumstances, with what I consider Dr. Carl's thinking a key contribution. I think the reason why it is so hard to predict patterns is that the context in which we live and operate is by and large very difficult to control. Individual choices are shaped by context as well as the recommendations of others. Which means you can help spread word of mouth so far. Social contagion makes the spreading easier, it does not make it more predictable.
Back to Watts. According to him, you mix a dose of old-school marketing with a dash of six-degree effects. Watts and his cohort, Jonah Peretti, have married mass ad buys with
technology like ForwardTrack, which displays the route the ad travels
once you've forwarded it using the "share with your friend" button. Just like the tracking software of social networks.
This allows them to see where the ad goes and how it moves thanks to those who keep it moving. These people, Watts says, may not necessarily be the most "important" in a network. The rationale is that since you do not know who's going to pass the ad on, you should aim as broad as possible. He's calling part of his research at Yahoo, where he works now, Big Seed marketing.
Let's say you are trying to build some buzz around your product or service. What I conclude from what both the white paper suggests and the article says:
- Focus less on who people influence and more on how people are influenced.
- Think more about networks, and network structure, rather than treating everyone as behaving independently (group dynamics).
- Move away from the idea that buzz can be engineered to achieve some pre-established outcome, and get better at measuring and reacting to buzz that arises naturally (observation from context).
This is a lot to digest in such a short space. I've seen talk around these very concepts on Twitter recently. How would you approach measurement? Do you agree on the findings on influence?
[Image: is the value of a social network defined also by who is excluded?]