The proliferation of social media platforms like Twitter has heightened theconsequences of the spread of misinformation . To understand and model thespread of misinformation, in this paper, we leveraged the SEIZ (Susceptible,Exposed, Infected, Skeptics) epidemiological model . Applying a mathematical model can help to understand the trends and dynamics of spread ofmisinformation on Twitter and ultimately help to develop techniques to quicklyidentify and control it . We analyzed misinformationregarding the unrest in Washington, D.C. in the month of March 2020 which waspropagated 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 model to the spread of aspecific item of misinformation in this research, which is distinct from that ofrumor, and a hoax on online social media sites. Applying this model is the

Author(s) : Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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Keywords : model - misinformation - spread - twitter - epidemiological -

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