loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ivan P. Yamshchikov and Sharwin Rezagholi

Affiliation: Max Planck Institute for Mathematics in the Sciences, Germany

Keyword(s): Electoral Competition, Classification of Political Issues, Dynamic Stochastic Blotto Game, Adaptive Learning.

Abstract: This paper employs a novel method for the empirical analysis of political discourse and develops a model that demonstrates dynamics comparable with the empirical data. Applying a set of binary text classifiers based on convolutional neural networks, we label statements in the political programs of the Democratic and the Republican Party in the United States. Extending the framework of the Colonel Blotto game by a stochastic activation structure, we show that, under a simple learning rule, the simulated game exhibits dynamics that resemble the empirical data.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.201.16.34

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Yamshchikov, I. and Rezagholi, S. (2018). Elephants, Donkeys, and Colonel Blotto. In Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS; ISBN 978-989-758-297-4; ISSN 2184-5034, SciTePress, pages 113-119. DOI: 10.5220/0006761601130119

@conference{complexis18,
author={Ivan P. Yamshchikov. and Sharwin Rezagholi.},
title={Elephants, Donkeys, and Colonel Blotto},
booktitle={Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS},
year={2018},
pages={113-119},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006761601130119},
isbn={978-989-758-297-4},
issn={2184-5034},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS
TI - Elephants, Donkeys, and Colonel Blotto
SN - 978-989-758-297-4
IS - 2184-5034
AU - Yamshchikov, I.
AU - Rezagholi, S.
PY - 2018
SP - 113
EP - 119
DO - 10.5220/0006761601130119
PB - SciTePress