Facebook, YouTube, Blogger--these social networks situate their "users" as both the producers and consumers of content. These forms of production (creating videos, profiles, etc.) and consumption (watching videos, browsing profiles) are free labor. The sum of this free labor -- logging in, spending time on the website -- is abstracted as "site traffic"and in other metrics of users' activity, which attracts advertisers who in turn exchange money for ad space/time on the site. Ad revenues thus abstract and valuate (as money) users' free labor.
The discrepancy between users' uncompensated labor and social networking sites' ad revenues is the site of an intervention in coding I'd like to examine: Burak Arikan & Engin Erdogan's User Labor Markup Language (ULML). ULML draws explicitly on Terranova's research (see footnote one at the link above) and seeks to measure a user's labor, which includes:
- generating assets (e.g. user profiles, images, videos, blog posts),
- creating metadata (e.g. tagging, voting, commenting etc.),
- attracting traffic (e.g. incoming views, comments, favourites)
- socializing with other people (e.g. number of friends, social influence)
Arikan and Erdogan present ULML as a way for social network users to demand compensation for the value they create. In their analysis, ULML exemplifies the kind of "universal, transparent, and self-controlled user labor metrics [that] will ultimately lead to a more sustainable social web." Yet the authors' insistence on transparency leads me to believe that they have taken up Terranova's analysis of free labor without delving into her equally important work on communication in network societies. For Terranova, communication is never simply a matter of exposing the truth or exposing facts to the light of reason. Terranova claims that
the power of communication and the media is not only the power of . . . forming a consensus . . . but also a biopolitical power, that is, a power of inducing perceptions and organizing the imagination, of establishing a subjective correspondence between images, percepts, affects and beliefs (152)Thus, the power of communication relies upon affective conditions that transparency alone does not satisfy. Furthermore, by abstracting, quantifying, rationalizing and valuing the affective labor that drives social networks, ULML obscures free labor's excessive source in affect (and not in a rationalized economic calculus), which ultimately gives such labor its transformative potential. Affect is thus twice missing : once in ULML's operation, and again in how its authors conceive of communication.
Another flaw of ULML is one that it shares with Viral Loop, a facebook application (among other things) that allows a user to calculate her friends' and her value on facebook based on certain parameters that, unlike in ULML, are not made available. This shared flaw is subjectivation. Both ULML and Viral Loop foreground users' production of value for social networking sites, but as a form of possibly political intervention, remain shortsightedly individualistic.
ULML was developed for Meta-Markets, a social networking website that allows users to "trade shares of social web assets from online bookmarking, social networking, photo and video sharing devices." Shares are not sold for real money (as opposed to Viral Loop, which calculates a user's value in U.S. dollars), and the project is pitched as a way to address users' "lack of awareness" about the value they generate, "keep[ing] the stream of this consciousness alive through community participation." Once again, we see the rhetoric of consciousness and awareness. But more to the point, Viral Loop, Meta-Markets and ULML divide the collective pool of users' labor into individual subjects who are then enjoined to increase their wealth relative to others' (Viral Loop, Meta-Markets) or to collaborate in order to demand individualized compensation (ULML).
By re-casting the networked multitude as a collection of competing or collaborating individuals, Viral Loop, Meta-Markets, and ULML enact the "subjectifying function that turns a multitude into an assemblage of isolated individuals" (126). Thus, the simultaneously pre-individual and collective potentialities of the multitude that Terranova invests with so much political promise are forsaken in favor of a kind of soft control, a "mode of capture of value produced by an increasingly interconnected and interdependent culture in as much as the latter is also an industry -- and hence a mode of labour" (128-9). Subjectifying functions "capture" part of the value of affective labor by quantifying that labor and making it exchangeable with capital (here we see the fundamental similarities of advertisers' and ULML, etc.'s operations). Yet Terranova claims that "this excessive value" of affective labor "can never be really reabsorbed in a logic of exchange and equivalence." (129) Understood in its fullest sense, the power of affective labor is "a power of making and remaking the world through the reinvention of life" (129).
For Terranova, this world-making power is at stake in our attempts to understand the affective labor of networked multitudes. While ULML, Meta-Markets and Viral Loop may indicate certain facts about free labor in the digital economy, their quantifying and subjectivizing operations do not provide the means necessary to harness that labor's power.