Adheat, Influence Scores, and Relevance Scores
The Adheat Model describes how advertisements might be passed around through a social network, from people who are perceived or scored as influencers, to the people whom they influence.
In some instances, once an opportunity to display an ad to a specific anonymous user has been awarded to an advertiser, an ad from the advertiser may be propagated from the user to the user's friends using a heat diffusion model. For instance, a user's influence on the social network can be represented as a heat intensity or a heat score, where users with more influence have a higher heat score. Propagation between users can then be modeled using a heat diffusion model. For example, an ad may spread (propagate) between two connected users as long as the user targeted with the ad has greater "heat" than the user yet to be targeted. This may result in ads propagating throughout the social network from more influential users to less influential users. One advantage that may be gained from the described method is the ability of advertisers to maximize advertising efficiency by propagating ads from influential users to influenced users.
While Google Plus may or may not carry advertisements some day, it's interesting to go through this patent, and get a better view of how people might be scored as "influencers" on a friendship graph, how it defines activity levels and influence levels.