As context, Li was talking how, beyond the contact lists, implicit data helps fill in gaps about the level of closeness or intimacy individuals have with each other. She went on to talk about how this will change in the future based on usage patterns detected by Google and other social networks... painting a picture of a future "social algorithm."

I don't disagree with Li's assertions at all - in fact I think she's spot on. It's the slide above that kept coming to mind. Taking that graphic at a literal level, I don't agree that the implicit data represented above really does help fill in gaps regarding people's relationships in any way other than a subjective one - nor do I think it reflects any kind of accurate indicator of an individual's level of "closeness" or "intimacy" with others (trust). Incidentally, I'm not sure Charlene actually asserted this... I believe the slide was used in a figurative manner.

But it still got me thinking about both sides of the trust equasion. How do individuals (specifically with regard to social media) think about trust with regard to other people?   How do marketers look at Trust in the networked economy?

For individuals, here's my take on what the trust spectrum might look like:



Playing off the concept of "circles of trust", we see an outward radiation of trust and intimacy.  At the "inner circle" there is high trust.  In the outer circle there is "no trust"  In further examining trust dynamics, it's fair to assert that people tend to transition back and forth between spheres, depending on events, mood, conversation, disposition and other factors.   

If you buy this concept, trust, or intimacy is therefore somewhat fluid. It's also device and technology independent (although the actions at the right of that diagram show how I might interact with individuals using social media terms).  We'll come back to this in at the end.


1. VOICE:  Understanding where an individual is trusted is an essential component of targeting. Voice examines an individual's level of engagement (posts, tweets, discussions, comments) across various topics (e.g. Frugal Living) and the overall sentiment of that engagement (positive, negative, neutral) over time.  In other words:  
For example, I might trust Beth Kanter as an authority on non-profits and social media.  However, I might not trust her as a good referral source on which flat screen TV I should buy.  As such, voice is a critical area of examination related to targeting high-trust individuals.


2. REACH: Examining the network of the individual is also an essential component of targeting. This includes an understanding of the person's online and offline influence, across traditional media channels (e.g. television, print, etc.).  In the online channels, reach examines the size and scope of the individual's active network within various sites and networks, as well as the frequency of communication that occurs. 


Furthermore, examining how the communication and dialog flows across online and offline channels may be germane to gauging the efficacy of an individual's reach. 

INFLUENCE:  There's been a lot of talk about influence today - and I don't want to rehash all that dialog. At a high level, and in simple terms, I see it as an outcome of a number of other considerations.  Primarily, I believe it is a measure of an individual's reach divided by the number of high trust relationships (see circle diagram above) times voice...something like this:


If influence directly impacted by the ebb and flow of trust within an individual's network, it it's important to note that influence is also somewhat fluid and relative. And all of this is already measured as a factor of time.

The sticky challenge is measuring the level of trust individuals have within their network. The truth is this: As outsiders, we can only gauge an individuals relationship on a trust spectrum based on a myriad of attributes, including length of relationship, messaging frequency, physical relationship, public/private discourse, "lists", discussion topic(s), sentiment, recent events, real-world connection and other complex and sometimes esoteric factors.  In the end, some of this data will be available and some will not.  As such, the outcome is somewhat likely to be somewhat subjective...depending on the time frame reviewed, quantity and amount of information analyzed (etc.).