  The proliferation of social media platforms like Twitter has heightened the
consequences of the spread of misinformation. To understand and model the
spread of misinformation, in this paper, we leveraged the SEIZ (Susceptible,
Exposed, Infected, Skeptics) epidemiological model to describe the underlying
process that delineates the spread of misinformation on Twitter. Compared to
the other epidemiological models, this model produces broader results because
it includes the additional Skeptics (Z) compartment, wherein a user may be
exposed to an item of misinformation but not engage in any reaction to it, and
the additional Exposed (E) compartment, wherein the user may need some time
before deciding to spread a misinformation item. We analyzed misinformation
regarding the unrest in Washington, D.C. in the month of March 2020 which was
propagated by the use of the #DCblackout hashtag by different users across the
U.S. on Twitter. Our analysis shows that misinformation can be modeled using
the concept of epidemiology. To the best of our knowledge, this research is the
first to attempt to apply the SEIZ epidemiological model to the spread of a
specific item of misinformation, which is a category distinct from that of
rumor, and a hoax on online social media platforms. Applying a mathematical
model can help to understand the trends and dynamics of the spread of
misinformation on Twitter and ultimately help to develop techniques to quickly
identify and control it.
