Social Contagion of Risk Perceptions in Environmental Management Networks

Abstract

An important requisite for improving risk communication practice related to contentious environmental issues is having a better theoretical understanding of how risk perceptions function in real-world social systems. Our study applied Scherer and Cho's social network contagion theory of risk perception (SNCTRP) to cormorant management (a contentious environmental management issue) in the Great Lakes Basin to: (1) assess contagion effects on cormorant-related risk perceptions and individual factors believed to influence those perceptions and (2) explore the extent of social contagion in a full network (consisting of interactions between and among experts and laypeople) and three "isolated" models separating different types of interactions from the full network (i.e., expert-to-expert, layperson-to-layperson, and expert-to-layperson). We conducted interviews and administered questionnaires with experts (e.g., natural resource professionals) and laypeople (e.g., recreational and commercial anglers, business owners, bird enthusiasts) engaged in cormorant management in northern Lake Huron (n = 115). Our findings generally support the SNCTRP; however, the scope and scale of social contagion varied considerably based on the variables (e.g., individual risk perception factors), actors (i.e., experts or laypeople), and interactions of interest. Contagion effects were identified more frequently, and were stronger, in the models containing interactions between experts and laypeople than in those models containing only interactions among experts or laypeople.

Where do Individuals Seek Opinions for Evacuation?A Case Study from Landslide-prone Slum Communities in Mumbai

“…One's perception about the possibility of landslide or possible losses is influenced by friends, relatives and co-workers living in the same neighborhood. The association between risk perception and interpersonal networks has also been reported by Scherer and Cho (2003) and very recently by Muter et al (2013).…”

“…Social intimacy, frequent interaction, and social norms all create shared contexts for information sharing and can be used to interpret prior behavior and attitudes that influence subsequent attitudes and behavior (Sagala et al, 2009;Bhandari et al, 2011;Townshend et al, 2014). Studies using this line of pursuit in disaster and other forms of risk management are rare (Scherer and Cho, 2003;Muter et al, 2013). Therefore, this study examines the evacuation behavior of Mumbai slum dwellers under landslide risks in light of the diffusion of innovation and social network approaches to provide a comprehensive social account of the evacuation behavior.…”

Agent-based computational modelling of social risk responses

“…The essence of the social amplification framework is that some risk event is experienced by a very small number of ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T 5 social actors, and communication about the risk then spreads through a system of heterogeneous actors seen as 'amplification stations' (Kasperson et al, 1988). Second, empirical work -notably Scherer and Cho's (2003) article and more recently Muter et al's (2013) in the risk literature, but also work such as that of Kohler et al (2007) in the demography literature -has shown how important social interactions are in the development of risk perceptions. An individual's risk beliefs tend to be strongly correlated to those of others with close social connections, and individuals' reports tend to acknowledge how those others have influenced them.…”

“…As suggested earlier, social risk amplification was from the start conceived as a communications phenomenon taking place in a network of 'amplification stations' of different kinds. And more recent work on risk perception (Scherer and Cho, 2003;Muter et al, 2013) has shown empirically that individuals' risk perceptions are strongly determined by their social connections. It therefore A C C E P T E D M A N U S C R I P T 8 seems essential that modelling should involve heterogeneous agents interacting within a social network.…”

“…In complex risk issues, the group of experts may well be ill-defined, consisting of independent academics, individuals employed by state regulatory agencies and those employed by commercial interests. There is evidence that expert risk beliefs converge with increasing inter-communication (Muter et al, 2013) but clearly in any particular case there may be no consensus. In what follows we assume a single, consensual expert assessment.…”