Relevance-Aware Flows

Originally posted in May 2008…

Just caught up to this post by Steve Gillmor and his take on the role, scale and reliability of Twitter as a communication/information switching platform.

Two things caught my attention.  First, positioning Twitter as a relevance-aware conversation soft switch… and second, defining a signal-to-noise for relevance of Twitter Flow as a function of who you follow, what topics you track and how you filter.

" At its simplest (its true power) Twitter is a phone switch for routing information flow. Those who control the flow control the price for the information. In a virtualized platform, the hardware is the razor and the software switch is the blades. The software switch is an affinity-based construct that manages the signal-to-noise ratio of the information flow based on the contouring signals (gestures) of the members of the group. In the language of Twitter, it’s who you follow times what you track divided by how you filter.

So, managing the signal-to-noise ratio for (twitter) Flows based on user or group gestures starts to define a relevance-aware flow of conversations or…

Relevance-Aware Flow = f( Following * Topics ) / Filter

One could imagine a number of different user-defined filters (think social, project, functional, process or other variables) used to identify and channel important conversation streams from within the Flow.

While the question of decentralizing Twitter as a method to improve scalability and performance is important, we shouldn't gloss over the need and value of filtering Flow into specific streams of relevant conversations and making them discoverable and social.

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