Opinion Leadership and Social Contagion in New Product Diffusion

Abstract

We study how opinion leadership and social contagion within social networks affect the adoption of a new product. In contrast to earlier studies, we find evidence of contagion operating over network ties, even after controlling for marketing effort and arbitrary systemwide changes. More importantly, we also find that the amount of contagion is moderated by both the recipients' perception of their opinion leadership and the sources' volume of product usage. The other key finding is that sociometric and self-reported measures of leadership are weakly correlated and associated with different kinds of adoption-related behaviors, which suggests that they probably capture different constructs. We discuss the implications of these novel findings for diffusion theory and research and for marketing practice.diffusion of innovations, opinion leadership, social contagion, social networks

Indicators of opinion leadership in customer networks: self-reports and degree centrality

“…This is surprising because by definition, opinion leaders should exert a disproportionate influence on others (King and Summers 1970). This finding complements the work by Iyengar et al (2011b) which shows that opinion leaders are less susceptible to influence from others, but that this relationship does not hold for sociometric leaders. We provide evidence which supports their suggestion that selfreported opinion leadership may signal self-confidence instead of actual opinion leadership.…”

Managing User-Generated Content: A Dynamic Rational Expectations Equilibrium Approach

“…Our work is related to the growing empirical literature in marketing on social networking and interaction (e.g., Ansari et al 2011;Stephen and Toubia 2010;Bulte 2007;Hartmann 2010;Nair et al 2010;Katona et al 2011;Iyengar et al 2011). Our work deviates from the social networking literature inasmuch as we consider user sites with large numbers of agents such that any single agent's participation is not likely to have a sizable effect on aggregate content consumption or generation.…”

The structure of online diffusion networks

“…Accordingly, theoretical models of diffusion have generally imitated disease models in the sense that popular products are assumed to diffuse multiple steps from their origin in the manner of epidemics, "infecting" large numbers of people in the process [Watts 2002;Leskovec et al 2006]. Although this assumption is entirely plausible, empirical diffusion research has historically relied on aggregate data, such as cumulative adoption curves [Coleman et al 1957;Bass 1969;Young 2009;Iyengar et al 2010], which reveal only the total number of adopters at any given time. While these curves are consistent with the hypothesis of "viral", disease-like diffusion, they are also consistent with other mechanisms, such as marketing or mass media [Van den Bulte and Lilien 2001].…”