Mining United Nations General Assembly Debates

Mateusz Grzyb; Mateusz Krzyziński; Bartłomiej Sobieski; Mikołaj Spytek; Bartosz Pieliński; Daniel Dan; Anna Wróblewska

Mining United Nations General Assembly Debates

Computation and Language 2024-06-21 v1 Information Retrieval

Authors: Mateusz Grzyb , Mateusz Krzyziński , Bartłomiej Sobieski , Mikołaj Spytek , Bartosz Pieliński , Daniel Dan , Anna Wróblewska

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Abstract

This project explores the application of Natural Language Processing (NLP) techniques to analyse United Nations General Assembly (UNGA) speeches. Using NLP allows for the efficient processing and analysis of large volumes of textual data, enabling the extraction of semantic patterns, sentiment analysis, and topic modelling. Our goal is to deliver a comprehensive dataset and a tool (interface with descriptive statistics and automatically extracted topics) from which political scientists can derive insights into international relations and have the opportunity to have a nuanced understanding of global diplomatic discourse.

Keywords

natural language processing text summarization large language model

Cite

@article{arxiv.2406.13553,
  title  = {Mining United Nations General Assembly Debates},
  author = {Mateusz Grzyb and Mateusz Krzyziński and Bartłomiej Sobieski and Mikołaj Spytek and Bartosz Pieliński and Daniel Dan and Anna Wróblewska},
  journal= {arXiv preprint arXiv:2406.13553},
  year   = {2024}
}

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4 pages, 1 figure, 2 tables

Mining United Nations General Assembly Debates

Abstract

Keywords

Cite

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