You might almost think that the whole scheme had been cooked up by a bunch of hyperintelligent but hopelessly socially naive people, and you would not be wrong. Asking computer nerds to design social software is a little bit like hiring a Mormon bartender. Our industry abounds in people for whom social interaction has always been more of a puzzle to be reverse-engineered than a good time to be had, and the result is these vaguely Martian protocols.
But the hyperintelligent people cooking up these ideas weren’t computer nerds (or, if they were, it was only because they were only R enthusiasts and LaTeX typography geeks on the side). As recovering sociologist Kieran Healy argues, the people to blame are in fact network sociologists.
As a disciplinary project, network theory has grown from a peripheral position in the early 1970s—or, more charitably, from its niche as a respected but specialized subfield—into a central project within contemporary sociology. Network theory has proliferated and diffused across the intellectual landscape over this period with great success. Its ability to cash out some of its most important theoretical concepts and images in formal methods and usable tools has been a vital part of this process. As in the case of theories of finance and their expression in financial markets, we see network theory and its analytical toolkit embedding and extending themselves in a range of settings. The growth of network theory within sociology, in other words, has been accompanied—and is perhaps by now overshadowed—by its practical embedding in the world at large.
… In the previous section we saw a range of Web 2.0 services that put calculative devices in the hands of users in interesting ways. These devices acted as “cognitive prostheses,” in Callon’s phrase—they allow users to do things they were unable to do before, such as easily see three or four degrees out of their social network, or discover which of thousands of strangers is most similar to them in their taste in books, or quickly locate people with similar financial goals, and so on. It is a relatively short step from here to taking advantage of these tools in ways that bear on actors’ conformity to some aspect of network theory. To take a simple but significant example, FaceBook uses its data on the global structure of the social graph to routinely suggest lists of “people you may know” to users, with goal of encouraging users to add those people to their network. In this way, the application works automatically to encourage the closure of forbidden triads in the network — something which, in theory, should be the case anyway — and likely also to increase the degree of measurable homophily in the network. Were a complacent analyst subsequently to acquire some portion of the FaceBook social graph and run some standard tests on the network’s structure without, they would find — to their satisfaction — some confirmatory results about the structure of “people’s social networks.
I should note that I switched a few days ago to Ceglowski’s Pinboard social bookmarking service, on the recommendation of Cosma Shalizi (who also prodded Kieran into finally putting that paper up on the WWW – no unclosed triads in this social graph …), and that it works very nicely, with a minimum of fuss.