https://orcid.org/0000-0002-3537-9036
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ABSTRACT
This article extends the field conceptualisation of social change and innovation adoption, which hinges upon the strategic capacities of actors, to the online environment. We focus on a key aspect of social movement organisations (SMOs), competition for members, resources and attention over an environmental risk issue. The incorporation of network theory enables us to map how the structural position of actors in the field is associated with their actions – for example, their response to an exogenous shock such as a new threat to the environment. We analyse how actors in the online environmental movement respond to the emergence of nanoscience and technology (NST) as a risk issue, and test the field theory hypothesis that dominated actors are more likely to adopt this issue in the early stages of emergence. Our findings challenge field theory orthodoxy and suggest that whilst challengers innovate, dominants co-opt by adopting the issue in a second stage. Finally, we examine why the notion that NST entails significant environmental and health risks was not propelled into wider public consciousness.
Acknowledgements
We thank all the reviewers who contributed to clarify our argument.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Mathieu O'Neil is Associate Professor in Communication at the University of Canberra's News & Media Research Centre and Adjunct Research Fellow in the School of Sociology at the Australian National University. His research and teaching are multidisciplinary, incorporating communication studies, the sociology of fields and controversies, social network analysis, and labour and organization studies. He is the founder of the online Journal of Peer Production.
Robert Ackland leads the Virtual Observatory for the Study of Online Networks (VOSON) Lab at the School of Sociology, Australian National University. With a background in economics, Robert works in the areas of network science and computational social science, with particular focus on online social and organisational networks.
Notes
1 See O’Neil and Ackland (Citation2019) for a discussion of the relationship between field theory, social network analysis and actor-network theory.
2 The length of time an actor has been present in the field is another possible proxy of challenger versus dominant status (and then we may refer to ‘new entrants’ and ‘incumbents’) but we choose to not use this measure here because new entrants are not necessarily of weak status.
4 The meta keywords were automatically processed before analysis (conversion to lower case, removal of numbers and stop words, etc.) and then words that could reasonably be identified as related to environmental issues were selected. Finally, synonyms were manually identifed.
5 Network analysis was conducted using the ‘igraph’ R package and Gephi was used for network visualisation.
6 The comparison cloud was drawn using the ‘wordcloud’ R package.
8 This conforms with Chateaureynaud’s (Citation2015) tracking of discourse relating to NST, where it was found that after being relatively unknown in the early 2000s, the issue spread through public arenas, including activist circles, in the years 2005–2006.
9 The analysis was conducted using the ‘survival’ package in R. The existence of right censoring (because the study ended before all sites had adopted the NST risk issue) is controlled for in the estimation approach. There is also one case of left truncation since ETC Group had already adopted the NST risk issue by the start of the data collection period in 2002 and it is therefore not known exactly when the adoption event occurred. The impact of left truncation was evaluated by removing this observation and re-running the survival model, and there was no qualitative difference in the results. Finally, there is also a potential problem of interval censoring since we only collected the website text content every two years (and we therefore do not know exactly when during the interval the event may have occurred); the potential impact of this type of censoring was not evaluated.
10 Other reasons for the absence of support for Hypothesis 2 are the sample’s relatively small size and lack of granularity (data collected only every 2 years).