Polansky, Alan M.
M.S. (Master of Science)
Department of Statistics and Actuarial Science
Social media has created a whole new framework in the way we understand ones expression of opinion, and how ones' opinion can influence others. Models of opinion dynamics, such as a probabilistic modeling framework of opinion dynamics over time are given by Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, and Manuel Gomez Rodriguez in ``Learning and Forecasting Opinion Dynamics in Social Networks." In this paper, we will continue to explore their models, now coming from a Bayesian statistical standpoint, specifically looking at the Approximate Bayesian Computation (ABC) method for the computation of better estimations for the data. We will then use kernal smoothing to represent our results graphically.
Bishop, Jessica L., "Exploring a Bayesian Analysis of Opinion Dynamics Using the Approximate Bayesian Computation Method" (2019). Graduate Research Theses & Dissertations. 6863.
Northern Illinois University
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