A-Kusmartseva.pdf (4.75 MB)
How can Trump win?
journal contribution
posted on 2018-01-15, 12:02 authored by Anna F. Kusmartseva, Wu Zhang, Xinyue Zhang, Feodor KusmartsevIn this paper, the McCulloch-Pitts model built on an artificial
neuron is first introduced briefly, followed by a modified model – the
coupled network model to describe social opinion network in period of the
presidential election. To illustrate the new model, its formalism and
analytical results on fixed points will be stated step by step. Then, we
investigate the dependence on the ratio of the initial conditions so that we
could find out more on relationship between current information and
preference on final results. Finally, U.S. election campaign in 2016 will be
examined comprehensively including support rates, possible preference,
time series analysis, and period analysis. Besides mathematical research,
we also take real-life activities into consideration. For example, Trump used
Twitter to help his view spreading and take advantage of the underlying
uncertainty to some extent.
History
School
- Business and Economics
Department
- Business
Published in
Hyperion International Journal of Econophysics & New EconomyCitation
KUSMARTSEVA, A.F. ... et al., 2017. How can Trump win? Hyperion International Journal of Econophysics & New Economy, 10(2), pp. 45-63.Publisher
© The Authors. Published by Hyperion UniversityVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2017Notes
This is an Open Access Article. It is published by Hyperion University under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND). Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/4.0/ISSN
2069-3508Language
- en