Weblogs as Deictic Systems

I would argue that this is part of the reason behind the upsurge in social software, for social networks provide us with an obvious analog for what we might term, paradoxically, "deictic systems." Our social networks are not necessarily technological, although certainly technologies play various roles in their constitution. More to the point, though, they are in constant flux, partly through our own activity (as we make efforts to meet new people and maintain contacts and relationships with the people we know) and partly also through serendipity (chance meetings, friend-of-a-friend introductions, etc.). A social network is sufficiently deictic, in fact, that it would be difficult to map even a single person's network fully before that network changed, albeit subtly.

While it's perhaps unremarkable to speak of social networks (or "networking") in a colloquial sense, it's worth asking whether or not there's a (potentially unbridgeable) gap between the colloquial, phatic "network" and the kinds of systems that Miller writes about. To put it more simply, do we each really possess social networks? Am I justified in seeing the collective group of my friends, nemeses, and acquaintances as a network per se, as opposed to an aggregate of the people who know me, some intentionally, some coincidentally, and some for a longer time than others?

The emerging field of network studies would answer this question affirmatively. Defining networks in the loosest possible terms (Duncan Watts, for instance, describes networks as "collection[s] of objects joined together in some fashion"), the scholars in this field span a range of disciplines, where they are slowly accumulating a series of network properties and behaviors that persist across dissimilar phenomena. Works like Watts' Six Degrees and Malcolm Gladwell's The Tipping Point, as well as any number of other network scholars, assert that there are indeed generalizable features to our social networks.

Watts, in particular, devotes considerable space in Six Degrees to the definition and explication of "small-world networks," so named for their ability to explain the small-world hypothesis:

The hypothesis was that the world, viewed as an enormous network of social acquaintances, was in a certain sense "small"; that is, any one person in the world could be reached through a network of friends in only a few steps. It was called the small-world problem, after the cocktail party banter in which two strangers discover that they have a mutual acquaintance and remind each other what a "small world" it is (38).

As Watts observes, it would be foolish to view our social networks as aggregates of individuals; "[W]e don't just have friends," he explains, "rather we have groups of friends...Within each group there will tend to be a high density of interpersonal ties, but ties between different groups will typically be sparse" (71). As Watts and his various colleagues began to try and model these networks, they identify two variables:

On the one hand, the network should display a large clustering coefficient, meaning that on average a person's friends are far more likely to know each other than two people chosen at random. On the other hand, it should be possible to connect two people chosen at random via a chain of only a few intermediaries. Hence, even globally separated individuals will be joined by short chains, or paths in the network (77-78).

On the face of things, these two variables would seem to be inversely related. The denser your cluster of relationships, the less time you would have to forge ties with other groups or clusters. And yet, Watts and Steve Strogatz discovered that these variables actually change at different rates, which means that there is indeed a class of networks where both the rate of clustering and the rate of connectivity are increasing: small-world networks.

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