SSOAR Logo
    • Deutsch
    • English
  • English 
    • Deutsch
    • English
  • Login
SSOAR ▼
  • Home
  • About SSOAR
  • Guidelines
  • Publishing in SSOAR
  • Cooperating with SSOAR
    • Cooperation models
    • Delivery routes and formats
    • Projects
  • Cooperation partners
    • Information about cooperation partners
  • Information
    • Possibilities of taking the Green Road
    • Grant of Licences
    • Download additional information
  • Operational concept
Browse and search Add new document OAI-PMH interface
JavaScript is disabled for your browser. Some features of this site may not work without it.

Download PDF
Download full text

(1.432Mb)

Citation Suggestion

Please use the following Persistent Identifier (PID) to cite this document:
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-62201-9

Exports for your reference manager

Bibtex export
Endnote export

Display Statistics
Share
  • Share via E-Mail E-Mail
  • Share via Facebook Facebook
  • Share via Bluesky Bluesky
  • Share via Reddit reddit
  • Share via Linkedin LinkedIn
  • Share via XING XING

ViEWS: A political violence early-warning system

[journal article]

Hegre, Håvard
Allansson, Marie
Basedau, Matthias
Colaresi, Michael
Croicu, Mihai
Fjelde, Hanne
Hoyles, Frederick
Hultman, Lisa
Högbladh, Stina
Jansen, Remco
Mouhleb, Naima
Muhammad, Sayyed Auwn
Nilsson, Desirée
Nygård, Håvard Mokleiv
Olafsdottir, Gudlaug
Petrova, Kristina
Randahl, David
Rød, Espen Geelmuyden
Schneider, Gerald
Uexkull, Nina von
Vestby, Jonas

Abstract

This article presents ViEWS - a political violence early-warning system that seeks to be maximally transparent, publicly available, and have uniform coverage, and sketches the methodological innovations required to achieve these objectives. ViEWS produces monthly forecasts at the country and subnati... view more

This article presents ViEWS - a political violence early-warning system that seeks to be maximally transparent, publicly available, and have uniform coverage, and sketches the methodological innovations required to achieve these objectives. ViEWS produces monthly forecasts at the country and subnational level for 36 months into the future and all three UCDP types of organized violence: state-based conflict, non-state conflict, and one-sided violence in Africa. The article presents the methodology and data behind these forecasts, evaluates their predictive performance, provides selected forecasts for October 2018 through October 2021, and indicates future extensions. ViEWS is built as an ensemble of constituent models designed to optimize its predictions. Each of these represents a theme that the conflict research literature suggests is relevant, or implements a specific statistical/machine-learning approach. Current forecasts indicate a persistence of conflict in regions in Africa with a recent history of political violence but also alert to new conflicts such as in Southern Cameroon and Northern Mozambique. The subsequent evaluation additionally shows that ViEWS is able to accurately capture the long-term behavior of established political violence, as well as diffusion processes such as the spread of violence in Cameroon. The performance demonstrated here indicates that ViEWS can be a useful complement to non-public conflict-warning systems, and also serves as a reference against which future improvements can be evaluated.... view less

Keywords
domestic security; political conflict; international conflict; conflict potential; conflict mediation; conflict resolution; conflict research; prevention; early warning system; Africa

Classification
Peace and Conflict Research, International Conflicts, Security Policy

Document language
English

Publication Year
2019

Page/Pages
p. 155-174

Journal
Journal of Peace Research, 56 (2019) 2

DOI
https://doi.org/10.1177/0022343319823860

ISSN
1460-3578

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution-NonCommercial 4.0


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.