Abstract
The quintessence of an individual’s taste is her aesthetic sensibility and system of preferences. Online social network profiles, such as those appearing on Friendster and MySpace, are a veritable “show and tell” for taste—allowing individuals to perform acts of taste by declaring their favorite books, what music they love, and what their passions are. By mining these social network profiles en masse and analyzing how each taste instance (e.g. a book, an author, a band, a cuisine, etc.) is meaningfully correlated with every other, an underlying fabric of taste common across individuals can be inferred. This article theorizes and describes the mining of taste fabrics from social network profiles, and discusses the application of taste fabrics to recommender systems and to taste-based semantic mediation. We suggest that taste fabrics illuminates a new paradigm of “sense-maker” services for the Semantic Web—homogenous connectionist networks such as taste fabrics provide ways to situate, compare, and unify entities along semantic dimensions which are normally hard to quantify, such as the taste dimension. Fuller expositions on the topic of this article can be found in (Liu & Maes, 2005a; Liu, Maes & Davenport, forthcoming).

Association of Information Systems SIG SEMIS Bulletin (Spring 2006), vol. 3 no. 1.
http://mf.media.mit.edu/pubs/journal/HomogeneityTaste.pdf