Correction

This article refers to:

Predicting (de-)escalation of sub-national violence using gradient boosting: Does it work?

Recurrent neural networks for conflict forecasting

Forecasting conflict using a diverse machine-learning ensemble: Ensemble averaging with multiple tree-based algorithms and variance promoting data configurations

High resolution conflict forecasting with spatial convolutions and long short-term memory

Challenging the status quo: Predicting violence with sparse decision-making data

Forecasting conflict in Africa with automated machine learning systems

United they stand: Findings from an escalation prediction competition

The role of governmental weapons procurements in forecasting monthly fatalities in intrastate conflicts: A semiparametric hierarchical hurdle model

Conflict forecasting with event data and spatio-temporal graph convolutional networks

A shape-based approach to conflict forecasting

Article title: “Challenging the Status Quo: Predicting Violence with Sparse Decision-Making Data”

Authors: Konstantin Bätz, Ann-Cathrin Klöckner, and Gerald Schneider

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2051024

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

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Article title: “Conflict Forecasting with Event Data and Spatio-Temporal Graph Convolutional Networks”

Authors: Patrick T. Brandt, Vito D’Orazio, Latifur Khan, Yi-Fan Li, Javier Osorio, and Marcus Sianan

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2036987

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

***

Article title: “A Shape-Based Approach to Conflict Forecasting”

Authors: Thomas Chadefaux

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2009821

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

***

Article title: “Forecasting Conflict in Africa with Automated Machine Learning Systems”

Authors: Vito D’Orazio and Yu Lin

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2017290

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

***

Article title: “Forecasting Conflict Using a Diverse Machine-Learning Ensemble: Ensemble Averaging with Multiple Tree-Based Algorithms and Variance Promoting Data Configurations”

Authors: Felix Ettensperger

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.1993209

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

***

Article title: “The Role of Governmental Weapons Procurements in Forecasting Monthly Fatalities in Intrastate Conflicts: A Semiparametric Hierarchical Hurdle Model”

Authors: Cornelius Fritz, Marius Mehrl, Paul W. Thurner, and Göran Kauermann

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.1993210

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

***

Article title: “Recurrent Neural Networks for Conflict Forecasting”

Authors: Iris Malone

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2016736

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

***

Article title: “High Resolution Conflict Forecasting with Spatial Convolutions and Long Short-Term Memory”

Authors: Benjamin J. Radford

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2031182

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.

***

Article title: “United They Stand: Findings from an Escalation Prediction Competition”

Authors: Paola Vesco, Håvard Hegre, Michael Colaresi, Remco Bastiaan Jansen, Adeline Lo, Gregor Reisch, and Nils B. Weidmann

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2029856

In the initially published article, due to an error in production, the formula for TADDA (Equation 3) was not readable as it overlapped with the text, and there was a typo in the conclusions. These issues are now corrected. References to the newly published articles in this Special Issue have also been updated.

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Article title: “Predicting (de-)Escalation of Sub-National Violence Using Gradient Boosting: Does It Work?

Authors: Jonas Vestby, Jürgen Brandsch, Vilde Bergstad Larsen, Peder Landsverk, and Andreas F. Tollefsen

Journal: International Interactions

DOI: https://doi.org/10.1080/03050629.2022.2021198

Citations to the articles introducing and comparing the contributions to the prediction competition special issue were missing in the initially published article. They are now added.