  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).
