<b>Malone</b>, E. L., M. Betsill, S. Hughes, R. Kemp, L. Lutzenhiser, M. Moezzi, B. L. Preston, and T. O. West, 2018: Chapter 6: Social science perspectives on carbon. In Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report [Cavallaro, N., G. Shrestha, R. Birdsey, M. A. Mayes, R. G. Najjar, S. C. Reed, P. Romero-Lankao, and Z. Zhu (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, pp. 264-302, https://doi.org/10.7930/SOCCR2.2018.Ch6.
Social Science Perspectives on Carbon
Social network analysis maps the connections among people who have links to one another. The focus is on the nature and strength of the links instead of on any characteristics of the individual members of the network. Examples of links relevant to the research include 1) “gives information to/receives information from,” 2) “has a similar worldview,” 3) “shares resources with,” or 4) “is a coauthor of.” Mapping the social network can provide insights about leadership and power structures.
6.8.1 Methods Used in Social Network Analysis
Social network analysis starts with a matrix drawn usually from a survey that shows the links among members of a defined social network. Software is used to both determine and display the linkages found, often with their strength, and to measure such characteristics as important nodes (i.e., centrality), density (i.e., out of the possible links, what is the proportion that actually exists?), and the length of certain pathways (e.g., through how many nodes must information go to get from one person to another?).
6.8.2 Applications to Carbon Cycle Research
Current relevant work, with few exceptions, does not focus on carbon but rather on climate change and disasters. Broadbent studies policy networks in the Comparing Climate Change Policy Networks project known as COMPON (see Broadbent and Vaughter 2014), which has teams in the United States, Canada, and Mexico (among other countries). Armitage et al. (2011) used social network analysis in case studies of co-management institutions for Canadian Arctic fisheries, finding that, over time, these networks co-produce knowledge, drawing on scientific and indigenous sources, that enables learning and adaptation. Malone (2009) used social network analysis to find shared elements of arguments (e.g., worldview, types of data used, authorities used, and solutions proposed) in the climate change debate, finding multiple connections even among analysts who make different arguments. Researchers also have studied disaster-response networks (Kinnear et al., 2013; Robins et al., 2011), where trust is a significant element in coordinated activity. Concerns about carbon link researchers and decision makers in complex networks, but these networks have not been mapped.
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