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Detecting Disruption: Identifying Structural Changes in the Verkhovna Rada

  • Thomas MagelinskiEmail author
  • Jialin Hou
  • Tymofiy Mylovanov
  • Kathleen M. Carley
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11549)

Abstract

We identify time periods of disruption in the voting patterns of the Ukrainian parliament for the last three convocations. We compare two methods: ideal point estimation (PolSci) and faction detection (CS). Both methods identify the revolution in Ukraine in 2014. The faction detection method also detects structural changes prior to the revolution (election of the president whose tenure was ended early by the revolution), while the ideal points method performs stronger after 2014, identifying a disruption around voting on constitutional changes to implement Minsk II agreements between separatists and Ukraine. The ideal point method is better at detecting position changes of the members of parliament, while the faction method is better at detecting changes in relationships between different MPs. The results suggest that after 2014, the Ukrainian parliament has become more consolidated, but the distribution of its political positions continues to evolve in response to changes in geo-political conditions.

Keywords

Change point analysis Ideal points Faction detection Verkhovna Rada Dynamic network analysis Ukraine 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.CASOS, Institute for Software ResearchCarnegie Mellon UniversityPittsburghUSA
  2. 2.Department of EconomicsUniversity of PittsburghPittsburghUSA

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