Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling

Research article (International Journal of Forecasting, 2023) · cited 10× · AI/ML

academia openalex:W4319871150

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Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling

Summary

Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling is a scholarly article^[1].

Key Facts

Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling's instance of is recorded as scholarly article^[2].

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Instance of scholarly article

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Authored by 2

Hee-Seok Oh, Seungwoo Kang

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Hee-Seok Oh, Seungwoo Kang

References

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Direct Wikidata claims

[2] ↑ Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling — instance of (P31): scholarly article. wikidata.org.

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[1] ↑ Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling is an instance of scholarly article (scholarly article) [P31, primary]. Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA

4ort.xyz Knowledge Graph. (2026). Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling. Retrieved May 24, 2026, from https://4ort.xyz/entity/forecasting-south-koreas-presidential-election-via-multiparty-dynamic-bayesian-modeling

MLA

“Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/forecasting-south-koreas-presidential-election-via-multiparty-dynamic-bayesian-modeling.

BibTeX

@misc{4ortxyz_forecasting-south-koreas-presidential-election-via-multiparty-dynamic-bayesian-modeling_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling}}, year = {2026}, url = {https://4ort.xyz/entity/forecasting-south-koreas-presidential-election-via-multiparty-dynamic-bayesian-modeling}, note = {Accessed: 2026-05-24}}

LLM prompt

According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling — https://4ort.xyz/entity/forecasting-south-koreas-presidential-election-via-multiparty-dynamic-bayesian-modeling (retrieved 2026-05-24)

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