Social Media: Distributed Influence Quantifying the Impact of Social Media - A New White Paper from Edelman

 

Screencapture from Jonny Bentwood's White Paper on measuring influence.

Dave Webb answered my musings about quantifying the intangible with a pointer to this report and observation.  Dave Webb said "I have always had a problem forcing something that is organic by nature into a mechanical straightjacket. I mean, they're not called "intangibles" for nuthin'!"  Nonetheless, he recognizes, like me, the importance of looking at intangibles in a disciplined way.   For me, the issue is not so much quantifying the intangible, but making that quantification a standard.

On Twitter, Kami Huyse pointed over to her reflections on this paper which lead me again to the paper itself. 

A new whitepaper by Jonny Bentwood, a PR consultant for Edelman, Distributed Influence: Quantifying the Impact of Social Media (pdf) starts the conversation and attempt to address a method to quantify influence. The white paper is based on a roundtable held last year with a number of social media experts.

There's a lot to digest here. And before even getting to the meat of the metrics, conceptual models, and ideas, the introduction provides a powerful case for using social media that is well articulated:

For the first time in history, technology has reached a point where everyone has a voice. This voice, articulated through social media, can be extremely powerful and can force individuals, companies and communities to change the way they behave.

In Edelman’s 2007 Trust Barometer, results showed that employees or ‘someone like me’ are trusted far more than any other group of people. Combining this with the advent of socialmedia tools such as blogs, Facebook and Twitter has made an individual’s voice louder than ever before. Consequently, the need to understand which individuals are the most trusted or have the loudest voice has become increasingly important. However, at present there is no agreed reliable process for identifying who these people are or for quantifying the online value of one person over another.

The paper goes on to explain that measuring influence on blogs by number of subscribers and how many people linked to it isn't longer a credible metric because people are using a variety of different social media tools to connect with their audiences.   The paper describes a "Social Media Index" that looks at other criteria beyond this including presence and participation and friends on other social networks such as Twitter, Facebook, etc as well as page rank.   The intent was a scoreboard, but a catalyst for discussion that might lead to defining exactly what influence is.

The white includes a summary of discussion from a roundtable of social media experts discussing the attributes and dimensions of influence and how it differs from other attributes, for example attention.   It also raises the question, "Is influence what should be measured?"    A pithy quote from Jeff Jarvis in the side bar answers, "Starters and spreaders of memes are the most influential people."  It also identifies some other types of meme behavior including meme adapter, meme contributor, and meme reader.   Maybe the phrase "meme lurker" is better?.  This is beginning resonates with online community roles in a way.

The most interesting part was the discussion about the ladder of engagement that is used by activists and how social media flips it.  The conclusion here:

The ideal scenario was to use this concept to determine the precise time and place when both the influencers and the influenced would like to be engaged. What the roundtable concluded was that a system equivalent to Myers Briggs was needed for micro-communications. This would enable people to
be able to map target media, meme creation, consumption and sharing habits.

A suggested starting point would be to further analyze Forester's Social Technographics - or what people do online.  (Colleague David Wilcox has written about the report here). 

The last bit of the report describes how online communication and collaboration has changed and presents the four distinct quadrants for communication and collaboration:

1) Controlled Communication: One-way tactics such as TV advertising, online advertising and
media relations that are great for branding and visibility, but are seldom collaborative

2) Open Communication
Online initiatives, such as viral videos, that are designed to generate discussion, but not necessarily produce a shared outcome

3) Controlled Collaboration
Programmes that facilitate participation but are more controlled, for example numerous efforts to solicit consumer generated ads

4) Conversational Collaboration
Win-win initiatives that open a dialogue toward reaching a broader goal

The report ends with some good discussion questions and a lot of it is still far away from using the real world.  The big question - as applied to nonprofits.

How does one use this information – such as the index, the identification of meme spreaders, adapters, commentators - to shape a communication strategy?

How does one use the information to shape an evaluation of your communication strategy?

How does one use the information for continuous learning about how to use social media as a strategy for reaching your organization's outcomes?

Comments

[ville vesterinen]

Really enjoyed reading your thoughts on social media and how it applies to worthy causes that Nonprofits push -really good stuff Beth! Will follow your blog and spread the word :)

[Beth Kanter]

thanks so much. I like what you wrote about the YES2.0 as related to brands.

[Danielle Brigida]

This is excellent information. Social media is great for empowering your audience but it's extremely hard to quantify.

[Dunan Work]

The reputation index looks like a good direction. However, I think that the ability to measure influence of blogs is still a lot more accurate than attempts to measure influence through most other social media. This is because blogs – and maybe to a lesser degree, Twitter -- are much more able to directly measure attention and influence. Counting number of friends on Friendster or contacts on LinkedIn is much less about real influence because those numbers can be controlled by the person being measured. It’s analogous to measuring influence on blogs by counting the number of blogs in the blogger’s own blogroll. In some cases, yes, number of friends does actually reflect influence, but currently there’s no way to tell who invited whom or how strong the connections actually are. Data on influence within social networks is actually there – in LinkedIn maybe especially – but it still hasn’t been pulled together to create a decent reputation indicator.

Distinguishing between meme starters, spreaders, commentators, and adopters sounds like especially useful information for creating a strategy to spread your own messages. But it also seems like a strategy that requires a lot of personal analysis (work), over time, and not something that’s so easy to stick into a computed index. ??

[Jonny Bentwood]

Hi Beth

Thanks for the link to the white paper. You have written a very good summary of the paper highlighting some of the key points. However, what I found most interesting is how you intend to use these concepts for the non profit sector.

In relation to Dunan's comment above, I truly believe that even though automation will get us down the road a short way, the greatest headway will come through 'hard work' engaging and understanding a target audience.

Look forward to reading more of your thoughts.

Jonny