What the study found
The article presents a new machine-readable dataset of public United Nations Security Council transcripts from 1946 to 2024. It includes more than 160,000 speeches and over 87 million words, with speaker identity, affiliation, and speaking order preserved.
Why the authors say this matters
The authors say the dataset offers unprecedented historical depth and can support research on global security norms, institutional discourse, and the relationship between language and international policy. The study suggests it can help analyze how different actors express security concepts over time.
What the researchers tested
The researchers built a dataset from every available public transcript of the Security Council and organized it in a machine-readable format. They demonstrated its analytical potential with three illustrative applications using traditional text analysis and transformer-based text analysis, a type of machine learning used to process language.
What worked and what didn't
The dataset appears to support detailed analysis across nearly eight decades of deliberations, including Cold War and post-Cold War periods. The examples shown examine the evolution of sovereignty from right to responsibility, the transformation of human rights discourse after the Cold War, and the identification of institutional champions of the humanitarian turn.
What to keep in mind
The abstract describes illustrative applications, so the results presented are examples of the dataset's analytical potential rather than a full evaluation of every possible use. Limitations are not described in the available summary.
Key points
- The article introduces a machine-readable dataset of UN Security Council public transcripts from 1946 to 2024.
- The dataset contains more than 160,000 speeches and over 87 million words.
- It preserves speaker identity, affiliation, and exact speaking order.
- The authors demonstrate three illustrative text-analysis applications involving sovereignty, human rights, and humanitarian discourse.
- The study says the resource can support research on global security norms and institutional discourse.
Disclosure
- Research title:
- UN Security Council transcript dataset spans 1946 to 2024
- Authors:
- Takuto Sakamoto, Tomoyuki Matsuoka, Hiroto Ito
- Institutions:
- The University of Tokyo, Tokyo University of the Arts, Tokyo University of the Arts, Tokyo University of the Arts
- Publication date:
- 2026-03-30
- OpenAlex record:
- View
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