This article is making me doubt some of my earlier conclusions about the role of the steering media. Habermas, I’ve got to concede, is dated. As much as skeptics would like to show how social media fails to ‘democratize’ media (not in the sense of being justly won by elections, but rather in the original sense of being mob ruled), the fragmentation is real and the public is reciprocally involved in its own narration.
What can then be said of the role of new media in public discourse? Here are some hypotheses:
- As a first order effect, new media exacerbates shocks, both endogenous and exogenous. See Didier Sornette‘s work on application of self-excited Hawkes process to social systems like finance and Amazon reviews. (I’m indebted to Thomas Maillart for introducing me to this research.) This changes the dynamics because rather than being Poisson distributed, new media intervention is strategically motivated.
- As a second order effect, since new media acting strategically, it must make predictive assessments of audience receptivity. New media suppliers must anticipate and cultivate demand. But demand is driven partly by environmental factors like information availability. See these notes on Dewey’s ethical theory for how taste can be due to environmental adaptation with no truly intrinsic desire–hence, the inappropriateness of modeling these dynamics straightforwardly with ‘utility functions’–which upsets neoclassical market modeling techniques. Hence the ‘social media marketer’ position that engages regularly in communication with an audience in order to cultivate a culture that is also a media market. Microcelebrity practices achieve not merely a passively received branding but an actively nurtured communicative setting. Communication here is transmission (Shannon, etc.) and/or symbolic interaction, on which community (Carey) supervenes.
- Though not driven be neoclassical market dynamics simpliciter, new media is nevertheless competitive. We should expect new media suppliers to be fluidly territorial. The creates a higher-order incentive for curatorial intervention to maintain and distinguish ones audience as culture. A critical open question here is to what extent these incentives drive endogenous differentiation, vs. to what extent media fragmentation results in efficient allocation of information (analogously to efficient use of information in markets.) There is no a priori reason to suppose that the ad hoc assemblage of media infrastructures and regulations minimizes negative cultural externalities. (What are examples of negative cultural externalities? Fascism, ….)
- Different media markets will have different dialects, which will have different expressive potential because of description lengths of concepts. (Algorithmic information theoretic interpretation of weak Sapir-Whorf hypothesis.) This is unavoidable because man is mortal (cannot approach convergent limits in a lifetime.) Some consequences (which have taken me a while to come around to, but here it is):
- Real intersubjective agreement is only provisionally and locally attainable.
- Language use, as a practical effect, has implications for future computational costs and therefore is intrinsically political.
- The poststructuralists are right after all. ::shakes fist at sky::
- That’s ok, we can still hack nature and create infrastructure; technical control resonates with physical computational layers that are not subject to wetware limitations. This leaves us, disciplinarily, with post-positivist engineering, post-structuralist hermeneutics enabling only provisional consensus and collective action (which can, at best, be ‘society made durable’ via technical implementation or cultural maintenance (see above on media market making), and critical reflection (advancing social computation directly).
- There is a challenge to Pearl/Woodward causality here, in that mechanistic causation will be insensitive to higher-order effects. A better model for social causation would be Luhmann’s autopoieisis (c.f Brier, 2008). Ecological modeling (Ulanowicz) provides the best toolkit for showing interactions between autopoietic networks?
This is not helping me write my dissertation prospectus at all.