IDEAS home Printed from https://ideas.repec.org/p/cam/camdae/2404.html
   My bibliography  Save this paper

Introducing a Global Dataset on Conflict Forecasts and News Topics

Author

Listed:
  • Mueller, H.
  • Rauh, C.
  • Seimon, B.

Abstract

This article provides a structured description of openly available news topics and forecasts for armed conflict at the national and grid cell level starting January 2010. The news topics as well as the forecasts are updated monthly at conflictforecast.org and provide coverage for more than 170 countries and about 65,000 grid cells of size 55x55km worldwide. The forecasts rely on Natural Language Processing (NLP) and machine learning techniques to leverage a large corpus of newspaper text for predicting sudden onsets of violence in peaceful countries. Our goals are to: a) support conflict prevention efforts by making our risk forecasts available to practitioners and research teams worldwide, b) facilitate additional research that can utilise risk forecasts for causal identification, and to c) provide an overview of the news landscape.

Suggested Citation

  • Mueller, H. & Rauh, C. & Seimon, B., 2024. "Introducing a Global Dataset on Conflict Forecasts and News Topics," Cambridge Working Papers in Economics 2404, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:2404
    Note: cr542
    as

    Download full text from publisher

    File URL: https://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe2404.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dominic Rohner & Mathias Thoenig, 2021. "The Elusive Peace Dividend of Development Policy: From War Traps to Macro Complementarities," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 111-131, August.
    2. Håvard Hegre & Paola Vesco & Michael Colaresi, 2022. "Lessons from an escalation prediction competition," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 521-554, July.
    3. Paola Vesco & Håvard Hegre & Michael Colaresi & Remco Bastiaan Jansen & Adeline Lo & Gregor Reisch & Nils B. Weidmann, 2022. "United they stand: Findings from an escalation prediction competition," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 860-896, July.
    4. Mueller, H. & Rauh, C. & Ruggieri, A., 2022. "Dynamic Early Warning and Action Model," Cambridge Working Papers in Economics 2236, Faculty of Economics, University of Cambridge.
    5. Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Peck, 2022. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 764-779, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Racek, Daniel & Thurner, Paul & Kauermann, Goeran, 2024. "Integrating Spatio-temporal Diffusion into Statistical Forecasting Models of Armed Conflict via Non-parametric Smoothing," OSF Preprints q59dr, Center for Open Science.
    2. Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
    3. Mueller, H. & Rauh, C. & Ruggieri, A., 2022. "Dynamic Early Warning and Action Model," Cambridge Working Papers in Economics 2236, Faculty of Economics, University of Cambridge.
    4. Aslihan Arslan, Romina Cavatassi, Marup Hossain, 2022. "Research Series 69: Structural and rural transformation and food systems: a quantitative synthesis for LMICs," IFAD Research Series 320720, International Fund for Agricultural Development (IFAD).
    5. Berman, Nicolas & Couttenier, Mathieu & Monnet, Nathalie & Ticku, Rohit, 2022. "Shutdown policies and conflict worldwide," Journal of Comparative Economics, Elsevier, vol. 50(1), pages 240-255.
    6. Lax-Martinez, Gema & Rohner, Dominic & Saia, Alessandro, 2022. "Threat of taxation, stagnation and social unrest: Evidence from 19th century sicily," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 361-371.
    7. Adhvaryu, Achyuta & Fenske, James & Khanna, Gaurav & Nyshadham, Anant, 2021. "Resources, conflict, and economic development in Africa," Journal of Development Economics, Elsevier, vol. 149(C).
    8. Augustin TAPSOBA, 2022. "Conflict prediction using Kernel density estimation," Working Paper 258fc89a-4ec3-4eef-a0ff-7, Agence française de développement.
    9. Daisuke Miyakawa & Kohei Shintani, 2020. "Disagreement between Human and Machine Predictions," IMES Discussion Paper Series 20-E-11, Institute for Monetary and Economic Studies, Bank of Japan.
    10. Marcantonio, Richard A., 2022. "Toxic diplomacy through environmental management: A necessary next step for environmental peacebuilding," World Development Perspectives, Elsevier, vol. 28(C).
    11. Nicolas Gatti & Kathy Baylis & Benjamin Crost, 2021. "Can Irrigation Infrastructure Mitigate the Effect of Rainfall Shocks on Conflict? Evidence from Indonesia," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 211-231, January.
    12. Christian Ochsner, 2023. "Hostility, Population Sorting, and Backwardness: Quasi-Experimental Evidence from the Red Army after WWII," CERGE-EI Working Papers wp768, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    13. Patrick Premand & Dominic Rohner, 2024. "Cash and Conflict: Large-Scale Experimental Evidence from Niger," American Economic Review: Insights, American Economic Association, vol. 6(1), pages 137-153, March.
    14. Galdo Virgilio & Acevedo Gladys Lopez & Rama Martin, 2021. "Conflict and the composition of economic activity in Afghanistan," IZA Journal of Development and Migration, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 12(1), pages 1-23, January.
    15. Yujun Zhou & Erin Lentz & Hope Michelson & Chungmann Kim & Kathy Baylis, 2022. "Machine learning for food security: Principles for transparency and usability," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(2), pages 893-910, June.
    16. Reilly Barry & Sam Hannah, 2022. "The distributional impact of the Sierra Leone conflict on household welfare," IZA Journal of Development and Migration, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 13(1), pages 1-41, January.
    17. Marup Hossain & Conner Mullally, 2022. "Using evaluation data to predict loan performance among poor borrowers: The case of BRAC’s asset transfer and microcredit programmes," Development Policy Review, Overseas Development Institute, vol. 40(3), May.
    18. Yu-Chin Hsu & Robert P. Lieli, 2021. "Inference for ROC Curves Based on Estimated Predictive Indices," Papers 2112.01772, arXiv.org.
    19. Gerda Asmus & Raphaël Franck, 2022. "State Capacity, National Economic Policies and Local Development: The Russian State in the Southern Urals," CESifo Working Paper Series 9616, CESifo.
    20. Siwan Anderson & Patrick Francois & Dominic Rohner & Rogerio Santarrosa, 2022. "Hidden hostility: donor attention and political violence," WIDER Working Paper Series wp-2022-147, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    Civil War; Conflict; Forecasting; Machine Learning; News Topics; Random Forest; Topic Models;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cam:camdae:2404. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jake Dyer (email available below). General contact details of provider: https://www.econ.cam.ac.uk/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.