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Here is an excellent, yet sobering, article by Leskovec, Adamic &  
Huberman about on-line opinion leadership and viral marketing...

> Firstly, it is frequently assumed in epidemic models that
> every time individuals interact they have equal probability
> of being infected. Contrary to this we observe that the prob-
> ability of infection decreases with repeated interaction. Mar-
> keters should take heed that even if viral marketing works
> initially, providing excessive incentives for customers to rec-
> ommend products could backfire by weakening the credibil-
> ity of the very same links they are trying to take advantage of.

> ...probability of purchasing a product increases with the num-
> ber of recommendations received, but quickly saturates to
> a constant and relatively low probability. This means that
> individuals are often impervious to the recommendations of
> their friends, and will resist buying items that they do not want.

>                                              In contrast, we find  
> that there are
> limits to how influential high degree nodes are in the recom-
> mendation network. As a person sends out more and more
> recommendations past a certain number for a product, the
> success per recommendation declines. This would seem to
> indicate that individuals have influence over a few of their
> friends, but not everybody they know.



On Jan 18, 2007, at 10:33 AM, Guy Hagen wrote:

>>> A unique value of the BuzzLogic service is its ability to gather  
>>> data and draw maps that show the network of trusted relationships  
>>> linking influential bloggers. Based on criteria established by  
>>> users, these maps show:
>>> Who is influencing specific topics, based on linking  
>>> relationships and other gestures participants make within  
>>> blogging conversations;
>>> How information flows between influencers and other participants  
>>> within specific conversation topics; and
>>> How these relationships change, both over time and in real time.
>>> Powering BuzzLogic maps is a patent pending method for indexing  
>>> and describing the conversations taking place within social  
>>> media. The method indexes the millions of publishers  
>>> participating in conversations and then applies advanced analytic  
>>> technologies to consider relationships between them and time to  
>>> gauge how information is being published, shaped, shared and  
>>> consumed. In turn, BuzzLogic quantifies the relative influence of  
>>> participants in conversations at moments in time and over time.
> Does this imply that they are bridging individual identities across  
> multiple social software sites?  I find that improbable, or at  
> least, highly limited by the the anonymized nature of internet  
> activity.  While not claiming to be typical, I probably belong to a  
> couple dozen fora, blogs, listservs, and other professional and  
> technical discourse sites, many using different email addresses and  
> "identities" (account names, signatures) as whim and convenience  
> dictated.
> General public/professional awareness of "online opinion leaders"  
> is increasing.  I'm beginning to see job postings with online  
> "opinion leader development" as a responsibility, especially in the  
> medical / biotech fields:
>> id=456c8a9f4a0780&qCountry=United%20Kingdom&pp=25&view=2&page=8
>>  Public Relations for BioMed Central: write and send press  
>> releases, press release telephone follow-up with journalists,  
>> journalist database management, build relationships with  
>> journalists, key opinion leader development, PR event management  
>> and other PR activity as appropriate
>> Director of US Medical Affairs:
>> ..Building and maintaining direct oversight of a medical science  
>> liaison group; opinion leader advocacy development; supporting  
>> and....

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