John Batelle provides further proof of the value found at the intersection of network graphs and conversation analytics.
We now have a number of graphs defined by aggregating links and conversations around social objects: web graphs ( e.g. Google), social graphs (e.g. Facebook), interest graphs (e.g. twitter), location graphs (e.g. foursquare).
"In short, Twitter knows who you are connected to, and what you (and they) are interested in.
Fashion that into a graph - the same kind of graph that powered Google's graph of web links, or Facebook's social graph - and all of a sudden you have a pretty powerful organizing principle for relevance in the Twitterverse."
John Batelle, Twitter's "Public Interest Graph"
We will see more network graphs being formed around a number of new and different social objects. In addition, new innovative ways to derive relevance from the social conversations across various network graphs will continue to emerge.
As MG Siegler points out in his recent take on the Facebook vs. Twitter battle...
"Social networks ... lose because they fail to innovate. Because they fail to stay ahead of the curve."
Expect to see continued innovation focused on ways to aggregate and analyze real-time conversations across network graphs... and... a consolidation across the layers of network graphs.