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He's got the power...

It looks like Todd Andrlik has automated the Power 150 list which highlights amalgamated rankings between a number of different tracking solutions - now that's more like it.

Of course, as the case study highlights, this ranking is based on "a proprietary ranking algorithm that uses Google PageRank, Technorati Ranking, Bloglines Subscriber Count, and his own personal rating on content and delivery"

So, Todd, care to share?  Is the Power about influence, reach, popularity or footprint?

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Map of Science...

This is a wonderful representation of location-based science papers:

"Data for this map is based on Thomson’s 2003 citation databases. The analytical procedure was hiearchical clustering using co-citation analysis. Visualization uses VxInsight, a proprietary software package from Sandia National Labs."

 

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See, M.O...

Strumpette has an interesting survey and take on from the CMO Council seeming to infer that 'PR 2.0' will be over in 2007, due to the fact that CMOs are looking to measure what matters and look at what matters only as what can be measured when it comes to aligning marketing with sales.  Of course, this assumes that you can't measure the impact 'PR 2.0' has online.  And companies implementing measurement dashboards can only be a good thing for the investment in measuring all marketing communications activities with equal weight...   

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I'm sorry I can't take your Twitter right now...

Whilst AutoTwit makes a humourous point on its site, there's also a serious message about the automation of populating the internet in a non-live fashion or indeed simply in an automated machine fashion. 

Whilst people can effectively spot and filter out splogs and link sites, there is still a level of influence that seeing these things on search engines adds to the subconscious.  Think about the number of results found on a particular issue when searched - if these sites are adding significantly to this number, it may well influence people's perception that the issue is more popular than they thought and therefore the believeability of sites found which are promoted to the front page of a search engine must be very popular and therefore quite influential.  Of course we know this not to be true.

When applications like AutoTwit kick in, we also don't know when a meme or story has been dropped in and whether it is in real time or not.  This application might be useful for releasing information under embargo for example, but it also negates the social and interactive nature of Twitter in terms of real-time information and being part of a community.  It is this immediacy of a cross between IM and blogging which has been appealing to people.  It is also seemingly the future of network-oriented interactive communications rather than static blog posts.  Something that makes social influence harder to measure online if this is the trend for the future.

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Gladwell not so glad...

Anastasia Goodstein's site has a piece posted by chet which points to an article in Harvard Business Review regarding the shift from Gladwell's theory of influence to a more nuanced theory.  The quote she highlights:

"First, they should focus less on who people influence and more on how people are influenced. It sounds like just the other side of the same coin, but the difference is important—identifying easily influenced people, and how they are influenced raises different questions, and requires different research design than looking for influentials. Second, they should also think more about networks, and network structure, rather than treating everyone as behaving independently. And third, they should move away from the idea that buzz can be engineered to achieve some prespecified outcome, and get better at measuring and reacting to buzz that arises naturally."

I strongly associate with this, for a number of reasons.  The reason why Gladwell's theory of influence worked when it did was precicely due to the fact that there was a limited supply of access to information, and thus a vacuum of informed opinion from which to source consultancy.  Easily influenced people would be swayed by fewer people.  Nowadays, with immediate access to information validated by groups, questions about what exactly constitutes the truth - as opposed to 'truthiness' which seems more important these days in the context of instant gratification and frequent change - and the global nature of peer review, this theory no longer represents the real world heirarchy.

The above theory of Duncan Watts of Columbia University - for it is his name on the paper - is much more credible in today's society.  In this sense, it is important to look at the transactional nature of consuming information online and how it travels through sites that influence people differently according to the social levers they push.  In this way, the buzz can be tracked and predicted and - dare I say it - possibly engineered to achieve some prespecified outcome. 

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Raw Hide...

There's an interesting post on Onalytica regarding how to evaluate buzz, stating that there are free tools out there (which we all know and love) which will help you see 'raw' buzz.  You know, the Technorati's, Blogpulse, Grokker, IceRocket, etc etc.

However, the post continues:

"One of the problems with measuring the levels of raw buzz are that raw buzz treats all voices with equal weight: 1 mention in a random MySpace blog and 1 mention in The NY Times online edition both count as 1 mention and contribute equally to the raw buzz level about a topic.

However, the impact of a mention in the NY Times is likely to be greater than being mentioned on a random MySpace blog. Why? Because NY Times carries more influence on most (if not all) topics than your average MySpace blog.

So in order to make more sense of buzz one needs to factor in the weight (influence) of the “buzzer”." 

Fair enough.  It goes on to discuss however sites with different influence:

"During the 14 days Pfizer appeared in the context of “blood pressure” in the NY Times, International Herald Tribune and Medgadget.com as well as a list of other online media. All of these 3 sites carry more influence on the topic of “blood pressure” than Businessweek.com – the most influential onlinepublication Merck was mentioned in during that period."

OK.  And what was the influence measure used to evaluate this particular take?

"The relative influence of the 4 sites, on the topic of “blood pressure” was measured to 4.02, 1.62, 1.42 and 1.20 respectively – measured over 120 days"

I find this explanation unsatisfactory.  I agree that different sites have different influence.  I agree that different sites will have different influence levels on people reading the 'buzz'.  However, I don't know how they have decided that buzz about Pfizer within these sites will have an influence on the right people who would be interested in this.  There is no explanation of how they find out who is reading the site, for how long, whether they return frequently, whether they believe what they're reading, whether they've changed their opinion or whether indeed they've read a story about it in other sites and it is part of a decision-making process.

I agree that there is a need for assessing or providing meaning to raw buzz and I'm pleased to see that they have an element of time factored into their analysis.  What again is striking is the claims made without any validation of the way in which they have defined 'social influence'.

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Complexity mastered...

Finally we start to see some commentary from the academic community around the complexity or lack of sitting behind marketeers endeavours to promote social marketing.

On Herd - the hidden truth about who we are there's discussion about a paper sociologist Prof Duncan Watts of Columbia  challenging "the simple 'influence' models that lie behind many of the Buzz-marketing businesses which have sprung up in recent years."

Mark Earls however points to research that uncovered eight types of influencer:

"In the (now infamous) case of Alison's new Mercedes, they tracked back all of the different types influence and influence on Alison which together resulted in a contented Ford Fiesta Owner becoming - in just 2 weeks - a rather surprised Mercedes A series owner. Stephen and Fiona traced at least 8 types of influencer and - now having applied it to a number of other categories - believe that not only can one individual play different influence roles in the same purchase but that different types of purchase have different types of influencer involved...much more complicated, you see."

So where does this leave us in terms of social influence?  Should we stop thinking about it because it's just too darn complicated to map?  Nope.  We need to create the tools to enable us to utilise the right channels to reach the right influencers.  After all, in PR, we don't target fishing publications with a complex technical white paper, even though we know that some technologists like hobbies outside of work.  Even in a network rather than channel-centric world, there are ways and there are ways.  We need to make sure that we can establish factually the best networks to utilise to hit the right influencers with something useful or enjoyable for them.  And to do that, we need models.

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National interests...

Data mining expert Matthew Hurst points to the resulting graphic of a 28,000 person strong survey by the BBC.

"The poll asked 28,000 people in 27 countries to rate a dozen countries plus the EU in terms of whether they have a positive or negative influence."

Does this impact on social influence online?  I think so.  Individuals bring strong and pre-formed opinions to sites which may derive from countries they feel have a positive or negative influence on the world.  This will impact on the way in which they interact with the site or network.  This will lead directly to whether they interact positively or negatively initially and will also require differing forces from social levers in order for them to change their position or be influenced by the site or network.

So there may only be a force of this sort required when it is obvious where the site originates or if it is clear that the people populating the network are from a particular territory.

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Full of widgetty goodness...

There's an interesting piece by one Steve Bridger here talking about how certain organisations are encouraging people to adopt and download widgets for positive social influence - to show that they are making a positive difference to the world.  He quotes Saar Gur, co-founder of Carebadges:

"We want to give people ‘badges’ to help them identify with a cause and have a positive social influence amongst their peers. We use our “impact meter” of impressions/awareness, donations/support to help recognise folks that use their popularity for good. The money [donations] will come later if we can give tools to those who want to create cool badges, email signatures, etc., and we focus on the social impact that each user has in recruiting new members…"

If everyone adopted widgets it would be so much easier to measure social influence!

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What's measured matters...

Finally, some higher profile questions regarding measurement and evaluation - albeit on what should be easier to measure than social influence - here at the Social Media Club.  Jason Chervokas highlights:

"Heather Green of Businessweek points out a gulf between comScore and Hitwise when it comes to measuring YouTube. According to comScore, US traffic to YouTube (as measured by unique visitors) climbed 2.6% from December to January. According to Hitwise that growth was a whopping 33%. How do you explain a 30% difference?"

Measurement industries by their very nature tend to work on proprietary elements which form the competitive edge that positions them one above the other when it comes to clients evaluating them and the transparency argued for within this post is understandible but likely to be a cry in the dark.

If it's this divergent when it comes to measuring traffic, just one potential social level in influencing people's decisions, if we don't look to an industry definition of social influence with multiple ingredients, we will wind up with clients being told multiple things by multiple suppliers.  Isn't it in our interests to develop something that stands up to industry and academic scrutiny and which data companies can then adopt to show consistency in benchmarking results before further data analysis muddies the waters?

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