Among the different texts on the topic of PageRank that we looked at, the two seminal papers by Larry Page and Sergey Brin; The Anatomy of a Large-Scale Hypertextual Web Search Engine and The PageRank Citation Ranking: Bringing Order to the Web, were quite astonishing to read in context… knowing what would eventually come from the work described in them. It’s rare to be able to understand such inspired research and witness it’s culturally transformative effect in such a short time.
Considering PageRank as an applied form of one possible cultural modality in the establishing of value, both reinforces its proven effectiveness but allows for further questions on what other applied models might be similarly impacting in the sphere of search technology.
We can understand the notion of PageRank as being modelled on academic citation (which it was) or as a specialized instantiation of culturally established modes of precedence and derivation… implemented within a textually governed system (which academic citation is itself in a sense). That is that a possible understanding of cultural value can be arrived at through the notions of something establishing precedence and in that precedence its value is defined by later derivations from it, or in the case of PageRank: “backlinks” and “inedges”. This is discreetly realized within academic citation because of respected standards established through peer review… which as Page points out is exceptional.
A non-search related example might be stylistic and conceptual derivation within art history or architecture, where a particularly unique or divergent form establishes value through subsequent and derivative works by other artists or architects. Considering this model alongside something like PageRank could be of particular significance when analyzing how cultural derivation often leads to recombinant forms that can at times eclipse their sources of derivation and then possibly offer reinforcement to those sources greater than first order derivation might assume. This could be thought of as a model of second or third order “backlinking” or backward recursion… not necessarily in the form of a looping conundrum like “rank sinking” as illustrated by Page in his paper, but as a backward cumulative effect.. perhaps establishing a separate ranking dimension like a “MashRank” that reinforces backlink weights through a successful mashup or recombinant entity derived from them.
While considering related models outside search, it becomes apparent that while the application of PageRank is powerful in its essentialism; being founded on a system structural / connective model (links) rather than content, its operating principle being relatively low level or infrastructural has it’s limitations.
Non-textual search / meta-link based PageRank
One could imagine an obvious progression from system structural models, textual/hypertextual, toward third tier or meta level linking models. Perhaps forming scaleable linking methods capable of similar ranking as PageRank, but based on visual or sound information alone. Inroads toward such eventual methods can perhaps already be seen in technologies like object recognition based search (Google Goggles). To go further one could imaging linking structures based solely on emotion, though the interface methods might only exist in proto-theoretical terms.