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How can Trump win?

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journal contribution
posted on 15.01.2018, 12:02 by Anna F. Kusmartseva, Wu Zhang, Xinyue Zhang, Feodor Kusmartsev
In 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 Economy

Citation

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 University

Version

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

2017

Notes

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

2069-3508

Language

en

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