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Unlike traditional demographic variables that are based on individual characteristics, social network analysis examines the various relationships between people. The basis of network analysis is to understand how actors are located within a network. Self reported data is collected to describe the degree of the knowledge and trust between each pair of participants in this study. Using methods from graph theory the resulting matrices are analyzed resulting in the assignment of degrees of connection among the participants. This research tests whether social networks can be used to predict food product adoption in a multi-country setting. The goal of this paper is to determine if variables that represent different aspects of group structure can better explain why some participants choose to adopt new food products, while others do not.


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