Social Network Analysis 101

Thank you so much for your very insightful response. From a social media marketing ROI standpoint, I believe this discussion is critical.

A little background: As you may know, my company, VMR, is a client of ScoutLabs, which, of course has just been acquired by Lithium. I believe the main reason the Lithium - ScoutLabs combination makes sense is because it addresses a fundamental problem that virtually all marketers are currently facing: We need to be able to measure and then demonstrate positive financial ROI from social media marketing investments. In other words, we need to be able to show to our clients that their investment in social media marketing is resulting in either (a) increased revenue or (b) decreased costs. Those two business objectives are really the only ones that matter to executives and shareholders.  So one way of doing that is to create online spaces that are social, that encourage brand advocacy and (most important) bring the voices online one step closer to opening their wallet as a paying customer. The online community expertise that Lithium brings to the table helps tremendously in this regard. 

So given that context, I think what we are talking about is doing whatever we can from an analytics standpoint to smooth the path from online conversations to online conversions. 

Specifically, we at VMR want to be able to "categorize" individuals online according to their relation to our client brands. Specifically, we want to be able to quickly identify (on a dynamic, real-time basis): 

• Influencers (Centers of Influence) 
• Potential Customers

In terms of identifying influencers (who can and often are potential customers), I see the following methods as being very useful:

• Social Network Analysis
• Web Analytics, such as the following, that are related to specific online posts authored by the influencer:
  •  # of on-topic posts by influencer
  •  Total Comment Count
  •  On-topic comment count
  •  Total Unique Commenters
  •  On-topic inbound links from other websites
  •  Total inbound links
  •  For forums: On-topic forum replies
  •  # of Retweets

In terms of identifying potential customers, it seems to me one's level of influence is less relevant than one's demographic, psychographic and (if the potential customer is a business) firmographic profile. It sounds as though you have come up with a method that will be very useful in terms of statistically inferring this information. To your suggestion of

• Textual Analysis of user-provided data using
  • Natural Language Processing (NLP)
  • Latent Variable Modeling (LVM)