Contrasting medium and genre on Wikipedia to open up the dominating definition and classification of geoengineering

Markusson, Nils Olof and Venturini, Tommaso and Laniado, David and Kaltenbrunner, Andreas (2016) Contrasting medium and genre on Wikipedia to open up the dominating definition and classification of geoengineering. Big Data and Society, 3 (2). pp. 1-17. ISSN 2053-9517

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Abstract

Geoengineering is typically defined as a techno-scientific response to climate change that differs from mitigation and adaptation, and that includes diverse individual technologies, which can be classified as either solar radiation management or carbon dioxide removal. We analyse the representation of geoengineering on Wikipedia as a way of opening up this dominating, if contested, model for further debate.We achieve this by contrasting the dominating model as presented in the encyclopaedic article texts with the patterns of hyper-link associations between the articles. Two datasets were created tracing the geoengineering construct on Wikipedia, shedding light on its boundary with its context, as well as on its internal structure. The analysis shows that the geoengineering category tends to be associated on Wikipedia primarily with atmospheric solar radiation management rather than land-based carbon dioxide removal type technologies. The results support the notion that the dominant model of defining and classifying geoengineering technology has been beneficial for solar radiation management type technologies more than for land-based carbon dioxide removal ones. The article also demonstrates that controversy mapping with Wikipedia data affords analysis that can open up dominating definitions and classifications of technologies, and offer resistance to their frequent naturalising and decontextualising tendencies. This work is in line with recent work on digital sociology, but the article contributes a new methodology and reports on the first empirical application of controversy mapping using Wikipedia data to a technology.

Item Type:
Journal Article
Journal or Publication Title:
Big Data and Society
ID Code:
81452
Deposited By:
Deposited On:
16 Sep 2016 13:42
Refereed?:
Yes
Published?:
Published
Last Modified:
19 Feb 2020 03:21