Discipline: Mathematics and Statistics
Subcategory: Social Sciences/Psychology/Economics
Caleb Ignace - East Tennessee State University
Co-Author(s): Tin Phan and Victor Moreno, Arizona State University, Phoenix, AZ Gabriela Navas, University of Los Andes, Bogotá, Colombia Christopher Kribs, University of Texas at Arlington, Arlington, TX Carlos Castillo-Garsow, Eastern Washington University, Cheney, WA
The current 2016 US presidential primary election, characterized by many unexpected results, provides an interesting context to study how voters are influenced in deciding who to support. We address this question by developing a class of models driven either by the effect of mass media or by social interaction among voters and members of the parties. The dynamics are modeled using four compartments with a transition matrix in describing the evolution of a discrete-time Markov chain. Each model is studied and fit to poll data from the 2012 and 2016 presidential elections using numerical methods. A comparison across elections indicates that the social influence of each group changes from one election to another, but response to media is similar in both cases. For future research, since both models assume what happens in the future is only dependent of what is going on in the present, we hope to extend these concepts to non-memoryless process.
Funder Acknowledgement(s): NSF https://www.nsf.gov/discoveries/disc_summ.jsp?cntn_id=138291; Above is the NSF REU site for MTBI.
Faculty Advisor: Christopher Kribs, firstname.lastname@example.org
Role: This REU research project was conducted along two other students (Tin Phan and Gabriela Navas). All aspects of the research was mostly done together, except for data collection, of which I was not involved in. I was mainly involved in analyzing the details of the person-to-person model: fitting to the data, sensitivity analysis, and explanation of results where my focus. I almost exclusively wrote the introduction. But I played just as an important part as the other two students with model formulation and the conclusion section.