30 Jun 09 Measuring influence – it is mostly indirect

Possibly by coincidence, this week’s Social Media Club question of the week is about measuring influence in social networking… and I just wrote a bit about that topic in the Web Analytics group:

On Mon, Jun 29, 2009 at 8:07 AM, Peter Kristof wrote:

Can anyone point me to some good resources (articles, blogs, tools, vendors,etc.) for research on measurement of social media / Web 2.0?

I invented some of the original buzz measurement stuff (now owned by Nielsen/Buzzmetrics) …

Analytics progress in this field is slow – it depends very much on understanding language, which is fundamentally lousy and not progressing very fast.  There is enormous ambiguity in the behavior and text it measures, which shouldn’t come as a surprise to anyone in web analytics.  Despite all the talk around sentiment and such, I’m still convinced that the most important metric is how many people are talking about a topic; any system that doesn’t focus on that is probably off the mark.  No. 2. is how influential those people could be.  I say “could be” because generally speaking, we only can identify influencers by their potential to influence (because they participate in a lot of discussions, across venues) than their actual influence.  Finally, I always pay attention to how such systems summarize what’s going on in social networks.  Two million postings and here are the 10 that are best representative – how did you pick those?

Beware of cool visualizations… any sort of self-organizing mapping of social media space usually will not to scale well.  There are some very hard graph problems behind them.  I think most vendors will admit that the eye candy is more useful for selling services than for delivering intelligence.

In terms of where things are going, I think we’re seeing more innovations in packaging and pricing, away from the big expensive solutions to smaller, lower-cost tools, rather than breakthroughs in the technology of measurement.  I suspect that will remain true for a while, if only because social media itself is evolving so fast that what works today is likely to be obsolete soon.

Analytics progress in this field is slow – it depends very much on understanding language, which is fundamentally lousy and not progressing very fast.  There is enormous ambiguity in the behavior and text it measures, which shouldn’t come as a surprise to anyone in web analytics.  Despite all the talk around sentiment and such, I’m still convinced that the most important metric is how many people are talking about a topic; any system that doesn’t focus on that is probably off the mark.  No. 2. is how influential those people could be.  I say “could be” because generally speaking, we only can identify influencers by their potential to influence (because they participate in a lot of discussions, across venues) than their actual influence.  Finally, I always pay attention to how such systems summarize what’s going on in social networks.  Two million postings and here are the 10 that are best representative – how did you pick those?

Beware of cool visualizations… any sort of self-organizing mapping of social media space usually will not to scale well.  There are some very hard graph problems behind them.  I think most vendors will admit that the eye candy is more useful for selling services than for delivering intelligence.

In terms of where things are going, I think we’re seeing more innovations in packaging and pricing, away from the big expensive solutions to smaller, lower-cost tools, rather than breakthroughs in the technology of measurement.  I suspect that will remain true for a while, if only because social media itself is evolving so fast that what works today is likely to be obsolete soon.

Nick