Estimating the outcome of UKs referendum on EU membership using e-petition data and machine learning algorithms

Clark, SD orcid.org/0000-0003-4090-6002, Morris, M orcid.org/0000-0002-9325-619X and Lomax, N orcid.org/0000-0001-9504-7570 (2018) Estimating the outcome of UKs referendum on EU membership using e-petition data and machine learning algorithms. Journal of Information Technology and Politics, 15 (4). pp. 344-357. ISSN 1933-1681

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 The Author(s). Published by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Keywords: EU referendum; e-petitions; estimation; machine learning
Dates:
  • Published: 2 October 2018
  • Accepted: 15 June 2018
  • Published (online): 1 August 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Translational Medicine (Leeds)
Funding Information:
FunderGrant number
ESRCES/L011891/1
Depositing User: Symplectic Publications
Date Deposited: 19 Oct 2018 13:44
Last Modified: 13 Dec 2018 12:22
Status: Published
Publisher: Taylor & Francis
Identification Number: https://doi.org/10.1080/19331681.2018.1491926

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