Publication Date
2019
Document Type
Dissertation/Thesis
First Advisor
Polansky, Alan M.
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Statistics and Actuarial Science
Abstract
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.
Recommended Citation
Bishop, Jessica L., "Exploring a Bayesian Analysis of Opinion Dynamics Using the Approximate Bayesian Computation Method" (2019). Graduate Research Theses & Dissertations. 6863.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/6863
Extent
55 pages
Language
eng
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
