Abstract
In this paper, we present a dataset of country mentions within the debates of the UN Security Council (UNSC). Using the corpus of the UNSC debates [6], we extract country mentions from the speeches and link them to the country of the speaker, creating a who-mentions-whom network at country level. This data can be used to identify geopolitical change events over time by tracking the evolution of number of country mentions over time, and detecting peak points.
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References
Grimmer, J., Stewart, B.M.: Text as data: the promise and pitfalls of automatic content analysis methods for political texts. Polit. Anal. 21(3), 267–297 (2013)
King, G., Lowe, W.: An automated information extraction tool for international conflict data with performance as good as human coders: a rare events evaluation design. Int. Organ. 57(3), 617–642 (2003)
Leskovec, J., Rajaraman, A., Ullman, J.: Mining of massive datasets, chapter 3, finding similar items, pp. 68–122. Cambridge University Press, 2nd edn. (2014)
Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Lingvisticae Investigationes 30, 3–26 (2007)
Palshikar, G.: Simple algorithms for peak detection in time-series (2009)
Schoenfeld, M., Eckhard, S., Patz, R., Meegdenburg, H., Pires, A.: The UN security council debates (2019). https://doi.org/10.7910/DVN/KGVSYH
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Ghawi, R., Pfeffer, J. (2022). Analysis of Country Mentions in the Debates of the UN Security Council. In: Pardede, E., Delir Haghighi, P., Khalil, I., Kotsis, G. (eds) Information Integration and Web Intelligence. iiWAS 2022. Lecture Notes in Computer Science, vol 13635. Springer, Cham. https://doi.org/10.1007/978-3-031-21047-1_10
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DOI: https://doi.org/10.1007/978-3-031-21047-1_10
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