A Naturalistic Multi-Agent Model of Word-of-Mouth Dynamics

Abstract

Word-of-mouth is the interpersonal process by which information about a product, and more generally an innovation, diffuses within a social system. Despite of the lack of empirical data on interpersonal communication, several stylized facts are identified and widely accepted. For instance, consumers actively search for information about products. Knowledge about incremental innovations diffuses notably quicker, because part of the knowledge is already available from previous innovations. Hence, existing models applied to word-of-mouth do not reproduce these stylized facts.

We propose an agent-based model in which word-of-mouth is described in a more realistic way. In this model, the representation of individuals’ knowledge relies on associative networks. Interactions are described as the motivated communication of the part of beliefs attached to social objects. Simulations illustrate the increased representativeness of the model, including active search for information and diffusion of incremental innovations. These experiments show an important change in the diffusion rate caused by active search for information.