Abstract
In this paper I explore the relationship between the production and the value of Big Data. In particular I examine the concept of social media ‘prosumption’—which has predominantly been theorized from a Marxist, political economic perspective—to consider what other forms of value Big Data have, imbricated with their often speculative economic value. I take the example of social media firms in their early stages of operation to suggest that, since these firms do not necessarily generate revenue, data collected through user contributions do not always realize economic value, at least in a Marxist sense, and that, in addition to their speculative value, these data have value beyond an economic valence. Instead I argue that in addition to their function as systems for accumulation, social media and their associated data have an affective value, related closely to their economic value, and demonstrate the efficacy of social media as systems designed for the appropriation and circulation of user attention.
Document Type
Article
Publication Date
9-19-2016
Digital Object Identifier (DOI)
https://doi.org/10.1177/2053951716640566
Funding Information
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author acknowledges generous support from the Department of Geography and Graduate School at the University of Kentucky. The research for this paper was also supported by a National Science Foundation Doctoral Dissertation Improvement Grant, Geography and Spatial Sciences Program, award number 1563265.
Repository Citation
Cockayne, Daniel G., "Affect and Value in Critical Examinations of the Production and ‘Prosumption’ of Big Data" (2016). Geography Faculty Publications. 11.
https://uknowledge.uky.edu/geography_facpub/11
Notes/Citation Information
Published in Big Data & Society, v. 3, issue 2, p. 1-11.
© The Author(s) 2016
This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).