EAGER: The Identification of Social Systems Trust: Theory and Experimental Validation

Arizona State University, Scottsdale AZ

Investigators

Abstract

The effect of social network contacts is generally believed to be much stronger than either advertising or online reputation/rating systems. There are many theoretical models that try to predict how opinions spread among individuals that trust each other, but the experimental evidence to back them quantitatively in a real setting is still elusive. This project aims to close the gap between the theory of opinion diffusion and the several empirical studies that have been made recently on social media data. The novel idea is to exploit the presence of influential nodes that are ?stubborn?, i.e. agents who trust only themselves, to determine how opinions fluctuate in the network as a result of their activities and the relative trust among all agents in the social network. The mathematical insights from the theoretical models of opinion diffusion indicate that stubborn agents excite the social system in such a way that reverberations of their opinions in comments from others can allow one to fit appropriate system equations to this phenomenon. Another key insight is that using steady state models is a more robust method to match real data, since the fluctuations of opinions are not directly observable, only the individual actions and comments are. This effort, if successful, would be akin to realizing a ?social network Radar,? capturing a tomographic image of the hidden medium of a social group mutual trust. Preliminary results in the case of the celebrated linear De Groot's opinion diffusion model applied to Facebook data show remarkably good agreement between the graph one can extract from our method and first-hand knowledge of the group analyzed. This is a high risk high payoff project as several questions still need to be answered and tested to verify the results.