February 05, 2013
Noyce Conference Room
Matthew O. Jackson (Department of Economics, Stanford University)
Abstract. We develop a new, simple model of word-of-mouth diffusion that we then fit to data that we collected in 43 rural villages in Karnataka in southern India. Based on this model we do several things. First, we use it to derive a new measure of how central a given node is in a network: diffusion centrality. Second, we show that the diffusion centrality of those individuals informed first is a strong and significant predictor of the eventual participation in a microfinance program in these villages.
We also show that this centrality measure significantly outperforms other standard centrality measures, such as degree centrality, betweenness centrality, eigenvector centrality, and Bonacich centrality. Fitting the model to the village data allows us to (i) infer relative roles of basic information transmission versus other forms of peer influence, and (ii) distinguish information passing by participants and non-participants. We find that participants are significantly more likely to pass information on to friends and acquaintances than informed non-participants. However, information passing by non-participants is still substantial and significant, accounting for roughly one-third of eventual informedness and participation. We also find that, once we have properly conditioned on an individual being informed, her decision to participate is not significantly affected by the participation of her acquaintances.
Purpose: Research Collaboration
SFI Host: Cris Moore
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