cific types of interdependency, such as friendship, kinship, financial exchange, dislike, sexual relationships, or relationships of beliefs, knowledge or prestige.” The entry continues: “Social network analysis views social relationships in terms of network theory about nodes and ties. Nodes are the individual actors within the networks, and ties are the relationships between the actors. The resulting graph-based structures are often very complex.” No kidding…I love the complexity and curiosity of my species—human beings—and these ways of conceiving social relationships often strike me as dismayingly reductive. They’re very useful within their bounds, but they are summary abstractions of the lyrical complexity of everyday social life. We had a very fruitful foray at this meeting into social recommendations and boundaries—the complexity of “friend relations” and “access control privileges”; the connections between objects via hash tables; and connections between people, their stuff, and other people’s stuff. We discussed these things as inadequate approximations for supporting the negotiated and fluid nature of social trust relationships and the subtle boundaries we negotiate with others.

Somewhat related, my col-
league with statistical train-
ing was excited to introduce
aggregate behavioral models
from activity data and collective
intelligence from explicit data
in our discussion about contem-
porary notions of “harnessing
the hive.” We pressed through
issues in database design and
the potential for data mining,
as well as the relevance, recom-
mendation, and algorithms for
automatically inferring buzz,
interest, and so on. Here, “social”
was to be found in the shadows
cast by humans clicking, clack-
ing, typing, uploading across
the interconnected networks of
the Internet, and making con-
nections betwixt and between
things that were heretofore not
there to be connected, or at least
not visibly so. We discussed how
we sometimes derive models—
hypotheses, really—about
behavior from these obscured
traces and how we are some-
times fooled into seeing patterns
where there in fact are none.