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Published:
Attended my co-author’s presentation of “A Cross-National Analysis of Forced Population Resettlement in Counterinsurgency Campaigns” at the European Peace Science Conference 2017.
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We presented “Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction” at the COMPTEXT conference 2022.
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Presented “ Do alliances deter civil conflict? Assessing the effect of military alliances on the onset of intrastate violence.” at the AFK Methods Empirical Research on Peace and Conflict Workshop 2022 (https://afk-web.de/cms/arbeitskreise-der-afk/arbeitskreis-methoden/).
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Presented “The Impact of Sanctions Imposition Coordination: A Time-Varying Measure of EU and US Sanctions Coordination in the Cases of Russia, Iran, and North Korea” at the COMPTEXT conference 2023.
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Attended my co-author’s presentation of “Friend or Foe: Using Aspect-Based Sentiment Analysis to Measure Relations between Member States at the UN General Assembly” at the European Peace Science Conference 2023.
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Presented “Friend or Foe: Using Aspect-Based Sentiment Analysis to Measure Relations between Member States at the UN General Assembly” at the AFK Methods Empirical Research on Peace and Conflict Workshop 2023 (https://afk-web.de/cms/arbeitskreise-der-afk/arbeitskreis-methoden/).
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Presented “The Promises and Pitfalls of using Text as Data for Crisis-Early Warning: A Comparative Assessment of NLP Methods for Conflict Prediction” at the Center for Crisis Early Warning Symposium 2023.
Published in Peace Economics, Peace Science and Public Policy, 2019
In this paper we study the use of Forced Population Resettlement in Counterinsurgency Campaigns.
Recommended citation: Böhmelt, Tobias, Dworschak, Christoph, Pilster, Ulrich and Walterskirchen, Julian. "A Cross-National Analysis of Forced Population Resettlement in Counterinsurgency Campaigns" Peace Economics, Peace Science and Public Policy, vol. 26, no. 1, 2020, pp. 20190022. https://doi.org/10.1515/peps-2019-0022 https://doi.org/10.1515/peps-2019-0022
Published in SpringerBriefs in International Relations, 2022
In this book, we analyse the complete life cycle of sanctions in three case studies.
Recommended citation: Walterskirchen, J., Mangott, G., Wend, C. (2022). Sanction Dynamics in the Cases of North Korea, Iran, and Russia: Objectives, Measures and Effects. SpringerBriefs in International Relations. doi:10.1007/978-3-031-17397-4 https://doi.org/10.1007/978-3-031-17397-4
Published in Political Analysis, 2023
In this paper, we introduce an interpretable deep learning approach to automatic dictionary creation for conflict research.
Recommended citation: Häffner, S., Hofer, M., Nagl, M., & Walterskirchen, J. (2023). Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction. Political Analysis, 31(4), 481-499. doi:10.1017/pan.2023.7 https://doi.org/10.1017/pan.2023.7
Replication report in SocArXiv , 2023
As part of the Nottingham Replication Games (I4R) we replicated “The morning after: cabinet instability and the purging of ministers after failed coup attempts in autocracies”.
Recommended citation: Oswald, C., Walterskirchen, J., Häffner, S., Binetti, M. N., & Dworschak, C. (2023, July 5). Replication of The Morning After: Report from the Nottingham Replication Games. https://doi.org/10.31235/osf.io/a2d5p https://doi.org/10.31235/osf.io/a2d5p
Replication report in EconStor , 2024
As part of the Replication Games (I4R) we replicated UN Peacekeeping and Democratization in Conflict-Affected Countries.
Recommended citation: Oswald, C., Walterskirchen, J. (2023, July 5). Computational and Robustness Reproducibility of UN Peacekeeping and Democratization in Conflict-Affected Countries. https://hdl.handle.net/10419/301427 https://hdl.handle.net/10419/301427
Accepted in Conflict Management and Peace Science , 2026
This paper evaluates the performance of features extracted from a conflict dictionary, two sentiment dictionaries, a word-scaling approach, dynamic topic models, and a transformer model on a classical conflict prediction task.
Recommended citation: Walterskirchen, J. (2026). Text as Data for Crisis-Early Warning: A Comparative Assessment of NLP Methods for Conflict Prediction. Conflict Management and Peace Science https://doi.org/10.1177/07388942261422045
Conditionally accepted in International Interactions , 2026
In this paper we predict conflict fatalities with temporal fusion transformers as part of the 2023/24 edition of the VIEWS Prediction Challenge.
Recommended citation: Walterskirchen J, Oswald C, Häffner S, Binetti MN. Taking time seriously: Predicting conflict fatalities using temporal fusion transformers. Conditionally accepted, International Interactions https://doi.org/10.31235/osf.io/7xu93_v2
Undergraduate course, University of Innsbruck, Department of Political Science, 2019
I was teaching the Proseminar Statistics for Sociel Sciences using R to undergraduate Sociology and Political Science students at the University of Innsbruck.
Undergraduate course, University of Innsbruck, Department of Political Science, 2020
I was teaching the Proseminar Statistics for Sociel Sciences using R to undergraduate Sociology and Political Science students at the University of Innsbruck.
Undergraduate Course, University of Innsbruck, Department of Political Science, 2020
I was teaching the Proseminar Applied Methods of Social Sciences to undergraduate Sociology and Political Science students at the University of Innsbruck.
Last updated: December 2023
In this paper, we investigate if coup risk is a better indicator for minister removals than failed coup attempt.
Recommended citation: Oswald, C., Walterskirchen, J., Häffner, S., Binetti, M.N., Dworschak, C. (in progress). The night before or the morning after: Coup risk, failed coup attempts, and minister removals in autocracies
Last updated: December 2023
In this paper, we compare different NLP approaches and their potential for improving conflict prediction
Recommended citation: Walterskirchen, J., Häffner, S. (in progress). The Promises and Pitfalls of using Text as Data for Crisis-Early Warning: A Comparative Assessment of NLP Methods for Conflict Prediction
Last updated: December 2023
In this paper, we seek to measure sanctions coordination between the US and the EU using NLP techniques.
Recommended citation: Walterskirchen, J., Häffner, S. (in progress). The Impact of Sanctions Imposition Coordination: A Time-Varying Measure of EU and US Sanctions Coordination in the Cases of Russia, Iran, and North Korea
Last updated: December 2023
This paper is part of the VIEWS prediction challenge.
Recommended citation: Walterskirchen, J., Häffner, S., Oswald, C., Binetti, M.N., Dworschak, C. (in progress). Enhancing Conflict Prediction: Investigating Temporal Dynamics and Spatial Dependencies through Deep Learning and Transformer-Based Architectures
Last updated: December 2023
In this paper, we investigate how countries apply different strategies of indiscriminate targeting.
Recommended citation: Dworschak, C., Walterskirchen, J. (in progress). The Toolkit of Indiscriminate Targeting: Forced Resettlement and Mass Killing
Last updated: December 2023
In this paper, we apply stance detection to UN General Assembly speeches.
Recommended citation: Häffner, S., Walterskirchen, J. (in progress). Hostile Rhetoric at the UN General Assembly: Using Aspect-Based Sentiment Analysis to Measure Relations between Member States