Publikation:

United They Stand : Findings from an Escalation Prediction Competition

Lade...
Vorschaubild

Dateien

Vesco_2-1hrlyvwq201dg3.pdf
Vesco_2-1hrlyvwq201dg3.pdfGröße: 5.75 MBDownloads: 65

Datum

2022

Autor:innen

Vesco, Paola
Hegre, Håvard
Colaresi, Michael
Jansen, Remco Bastiaan
Lo, Adeline
Reisch, Gregor

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

ArXiv-ID

Internationale Patentnummer

Link zur Lizenz

Angaben zur Forschungsförderung

European Union (EU): 694640

Projekt

Open Access-Veröffentlichung
Open Access Hybrid
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

International Interactions. Taylor & Francis. 2022, 48(4), pp. 860-896. ISSN 0305-0629. eISSN 1547-7444. Available under: doi: 10.1080/03050629.2022.2029856

Zusammenfassung

This article presents results and lessons learned from a prediction competition organized by ViEWS to improve collective scientific knowledge on forecasting (de-)escalation in Africa. The competition call asked participants to forecast changes in state-based violence for the true future (October 2020–March 2021) as well as for a held-out test partition. An external scoring committee, independent from both the organizers and participants, was formed to evaluate the models based on both qualitative and quantitative criteria, including performance, novelty, uniqueness, and replicability. All models contributed to advance the research frontier by providing novel methodological or theoretical insight, including new data, or adopting innovative model specifications. While we discuss several facets of the competition that could be improved moving forward, the collection passes an important test. When we build a simple ensemble prediction model—which draws on the unique insights of each contribution to differing degrees—we can measure an improvement in the prediction from the group, over and above what the average individual model can achieve. This wisdom of the crowd effect suggests that future competitions that build on both the successes and failures of ours, can contribute to scientific knowledge by incentivizing diverse contributions as well as focusing a group’s attention on a common problem.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
320 Politik

Schlagwörter

Conflict, escalation, forecasting, political violence, prediction

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690VESCO, Paola, Håvard HEGRE, Michael COLARESI, Remco Bastiaan JANSEN, Adeline LO, Gregor REISCH, Nils B. WEIDMANN, 2022. United They Stand : Findings from an Escalation Prediction Competition. In: International Interactions. Taylor & Francis. 2022, 48(4), pp. 860-896. ISSN 0305-0629. eISSN 1547-7444. Available under: doi: 10.1080/03050629.2022.2029856
BibTex
@article{Vesco2022-07-04Unite-57014,
  year={2022},
  doi={10.1080/03050629.2022.2029856},
  title={United They Stand : Findings from an Escalation Prediction Competition},
  number={4},
  volume={48},
  issn={0305-0629},
  journal={International Interactions},
  pages={860--896},
  author={Vesco, Paola and Hegre, Håvard and Colaresi, Michael and Jansen, Remco Bastiaan and Lo, Adeline and Reisch, Gregor and Weidmann, Nils B.}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/57014">
    <dcterms:title>United They Stand : Findings from an Escalation Prediction Competition</dcterms:title>
    <dc:creator>Weidmann, Nils B.</dc:creator>
    <dc:creator>Vesco, Paola</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-28T08:10:02Z</dcterms:available>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57014/1/Vesco_2-1hrlyvwq201dg3.pdf"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/42"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57014/1/Vesco_2-1hrlyvwq201dg3.pdf"/>
    <dc:contributor>Lo, Adeline</dc:contributor>
    <dc:contributor>Weidmann, Nils B.</dc:contributor>
    <dc:contributor>Hegre, Håvard</dc:contributor>
    <dc:creator>Jansen, Remco Bastiaan</dc:creator>
    <dcterms:issued>2022-07-04</dcterms:issued>
    <dc:contributor>Jansen, Remco Bastiaan</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-28T08:10:02Z</dc:date>
    <dc:contributor>Reisch, Gregor</dc:contributor>
    <dc:contributor>Vesco, Paola</dc:contributor>
    <dc:creator>Colaresi, Michael</dc:creator>
    <dc:contributor>Colaresi, Michael</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/42"/>
    <dc:language>eng</dc:language>
    <dc:creator>Hegre, Håvard</dc:creator>
    <dc:creator>Reisch, Gregor</dc:creator>
    <dc:creator>Lo, Adeline</dc:creator>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/57014"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dcterms:abstract xml:lang="eng">This article presents results and lessons learned from a prediction competition organized by ViEWS to improve collective scientific knowledge on forecasting (de-)escalation in Africa. The competition call asked participants to forecast changes in state-based violence for the true future (October 2020–March 2021) as well as for a held-out test partition. An external scoring committee, independent from both the organizers and participants, was formed to evaluate the models based on both qualitative and quantitative criteria, including performance, novelty, uniqueness, and replicability. All models contributed to advance the research frontier by providing novel methodological or theoretical insight, including new data, or adopting innovative model specifications. While we discuss several facets of the competition that could be improved moving forward, the collection passes an important test. When we build a simple ensemble prediction model—which draws on the unique insights of each contribution to differing degrees—we can measure an improvement in the prediction from the group, over and above what the average individual model can achieve. This wisdom of the crowd effect suggests that future competitions that build on both the successes and failures of ours, can contribute to scientific knowledge by incentivizing diverse contributions as well as focusing a group’s attention on a common problem.</dcterms:abstract>
    <dc:rights>Attribution-NonCommercial-NoDerivatives 4.0 International</dc:rights>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/4.0/"/>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Ja
Diese Publikation teilen