No Cover Image

Journal article 604 views 45 downloads

On revolutions

Armand M. Leroi Orcid Logo, Ben Lambert Orcid Logo, Matthias Mauch Orcid Logo, Marina Papadopoulou Orcid Logo, Sophia Ananiadou, Staffan I. Lindberg Orcid Logo, Patrik Lindenfors

Palgrave Communications, Volume: 6, Issue: 1

Swansea University Author: Marina Papadopoulou Orcid Logo

  • 59583.pdf

    PDF | Version of Record

    © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License

    Download (2.19MB)

Abstract

Sometimes the normal course of events is disrupted by a particularly swift and profound change. Historians have often referred to such changes as “revolutions”, and, though they have identified many of them, they have rarely supported their claims with statistical evidence. Here, we present a method...

Full description

Published in: Palgrave Communications
ISSN: 2055-1045
Published: Springer Science and Business Media LLC 2020
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa59583
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: Sometimes the normal course of events is disrupted by a particularly swift and profound change. Historians have often referred to such changes as “revolutions”, and, though they have identified many of them, they have rarely supported their claims with statistical evidence. Here, we present a method to identify revolutions based on a measure of multivariate rate of change called Foote novelty. We define revolutions as those periods of time when the value of this measure is, by a non-parametric test, shown to significantly exceed the background rate. Our method also identifies conservative periods when the rate of change is unusually low. We apply it to several quantitative data sets that capture long-term political, social and cultural changes and, in some of them, identify revolutions — both well known and not. Our method is general and can be applied to any phenomenon captured by multivariate time series data of sufficient quality.
College: Faculty of Science and Engineering
Funders: B.L. was supported by EPSRC grant code: EP/F500394/1. V-Dem data collection was supported by European Research Council, Grant 724191; Riksbankens Jubileumsfond, Grant M13-0559:1; Knut and Alice Wallenberg Foundation to Wallenberg Academy Fellow, Grant 2013.0166; as well as by internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg and the Marianne and Marcus Wallenbergs Foundation Grant 2017.0049.
Issue: 1