Models for the Diffusion of Beliefs in Social Networks: An Overview

Our article compared models for social learning and opinion diffusion in the context of economics and social science with those used in signal processing over networks of sensors, explaining how learning emerges or fails to emerge in both scenarios. It also critically discusses how the advent of the Internet and of smartphones is generating a wealth of data and enhancing the decision-making capabilities of social agents in ways that were never conceivable before. The article also argues that more engineering research is needed to advance modeling and inference algorithms and enhance even further the cyberinteractions of social agents. This area has tremendous potential as well as carries tremendous risks. Consumers lose their privacy and can be influenced in undesired ways. Hence, a critical consideration to make in expanding our understanding on this subject is to what extent it is safe to increase the ability of hardware and software to capture contextual data about the customers.

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