I Still Haven't Found what I'm Looking for: Predicting Security-Related Incidents and Conflict Fatalities with Google Trends and Wikipedia Data.
Conflict forecasting has seen two recent developments: a shift to predicting continuous variables and a debate about the value of structural and procedural variables. This paper contributes to these efforts and proposes the category of salience variables in the form of Google Trends and Wikipedia da...
| Publicado en: | Journal of Conflict Resolution Vol. 70; no. 2/3; pp. 499 - 525 |
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| Formato: | Artículo |
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Sage Publications Inc.
Feb/Mar2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=190751943&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 190751943 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00220027 JCF jtl: Journal of Conflict Resolution issn: 00220027 maglogo: Y pubinfo: dt: Feb/Mar2026 vid: 70 iid: 2/3 pid: 344 pub: Sage Publications Inc. artinfo: ui: 190751943 10.1177/00220027251362832 ppf: 499 ppct: 26 formats: tig: atl: I Still Haven't Found what I'm Looking for: Predicting Security-Related Incidents and Conflict Fatalities with Google Trends and Wikipedia Data. aug: au: Oswald, Christian affil: Center for Crisis Early Warning, University of the Bundeswehr Munich, Neubiberg, Germany su: Wikipedia Conflict management Searching behavior Real-time computing Security systems Predictive validity Risk assessment Independent variables sug: subj: Conflict management Security Systems Services (except Locksmiths) Searching behavior Real-time computing Security systems Predictive validity Risk assessment Independent variables Wikipedia keyword: civil wars conflict fatalities conflict intensity internal armed conflict prediction civil wars conflict fatalities conflict intensity internal armed conflict prediction ab: Conflict forecasting has seen two recent developments: a shift to predicting continuous variables and a debate about the value of structural and procedural variables. This paper contributes to these efforts and proposes the category of salience variables in the form of Google Trends and Wikipedia data. Internet searches can be precursors of conflict intensity as a result of for example an increase in protests, violent behavior, or public announcements. Data are readily and openly available, updated in real time, and provide global coverage which makes it ideal for near-real time forecasting. Prediction targets are the number of security-related incidents and battle-related, non-state, and civilian casualties. I demonstrate the value of salience variables using various out-of-sample windows and performance metrics on the country- and province-month level. I find evidence that salience variables have considerable predictive power, outperform other commonly used variables, and are thus a valuable addition to the conflict forecasting toolkit. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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