Is Uncertainty Always Bad?: Effect of Topic Competence on Uncertain Opinions

TL;DR

This paper investigates how the quality and quantity of uncertain information influence opinion formation and diffusion in social networks, revealing that high uncertainty isn't always detrimental if agents are sufficiently competent.

Contribution

It introduces a model using Subjective Logic to analyze the impact of mixed evidence types on opinions and demonstrates through simulations that agent competence moderates the effects of uncertainty.

Findings

High uncertainty can be beneficial if agents are competent.

The ratio of evidence types significantly affects opinion dynamics.

Agent competence reduces bias from uncertain information.

Abstract

The proliferation of information disseminated by public/social media has made decision-making highly challenging due to the wide availability of noisy, uncertain, or unverified information. Although the issue of uncertainty in information has been studied for several decades, little work has investigated how noisy (or uncertain) or valuable (or credible) information can be formulated into people's opinions, modeling uncertainty both in the quantity and quality of evidence leading to a specific opinion. In this work, we model and analyze an opinion and information model by using Subjective Logic where the initial set of evidence is mixed with different types of evidence (i.e., pro vs. con or noisy vs. valuable) which is incorporated into the opinions of original propagators, who propagate information over a network. With the help of an extensive simulation study, we examine how the different ratios of information types or agents' prior belief or topic competence affect the overall information diffusion. Based on our findings, agents' high uncertainty is not necessarily always bad in making a right decision as long as they are competent enough not to be at least biased towards false information (e.g., neutral between two extremes).