image: history flow edit log of the Wikipedia article on evolution
Nick Matzke is ambitious when he exercises his imagination. In answering our final question, Matzke sketches out a methodology for tracking how public policies or scientific hypotheses were “copied, repeated, modified and propagated” to see how society (and the passage of time) nurtures the spread of ideas. Matzke rightly points to memetics as an important precedent and it is clear that this reference, when coupled with his earlier call for docuinformatics (data driven historical scholarship) clearly illustrates a desire to quantify and track the evolution of conceptual models—no small task. We do have one great example of a “discourse tracker” with Wikipedia where popular articles undergo thousands of revisions which are all logged and timestamped. Visualization projects such as history flow (2003), clearly delineate the manner in which these documents are “collaborative constructions” that provides stark contrast compared to, for example, the singular genius evidenced in Ben Fry’s visualization of Charles Darwin’s sequential revisions to The Origin of Species [discussed on RevMinds here]. It is interesting to read between the lines of Matzke’s commentary on docuinformatics though, while he is clearly interested in big data and computational history, many of the techniques and types of analysis he is describing could be found in contemporary public relations. Think about it, real time trend analysis monitoring chatter across various social networks and microblogging services—Matzke essentially wants to apply this same scrutiny to the entire corpus of archived documents. It is an insanely ambitious proposal that would democratize knowledge production by diffusing “sole authorship” in favour of recognizing incremental advances. Matzke is not hyperbolizing when he states “the sky is the limit” for this kind of analysis as it could provide a fascinating reconsideration of knowledge production and decision making as a collective activity.