Complex Politics: A Quantitative Semantic and Topological Analysis of UK House of Commons Debates
원문 초록
This study is a first, exploratory attempt to use quantitative semantics techniques and topological analysis to analyze systemic patterns arising in a complex political system. In particular, we use a rich data set covering all speeches and debates in the UK House of Commons between 1975 and 2014. By the use of dynamic topic modeling (DTM) and topological data analysis (TDA) we show that both members and parties feature specific roles within the system, consistent over time, and extract global patterns indicating levels of political cohesion. Our results provide a wide array of novel hypotheses about the complex dynamics of political systems, with valuable policy applications.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Comparing the Effects of Persistence Barcodes Aggregation and Feature Concatenation on Medical Imaging
Topological Machine Learning for Protein-Nucleic Acid Binding Affinity Changes Upon Mutation
Topology across Scales on Heterogeneous Cell Data
Short-PHD: Detecting Short LLM-generated Text with Topological Data Analysis After Off-topic Content Insertion
A Topological Data Analysis Framework for Quantifying Necrosis in Glioblastomas
Persistent Homology-induced Graph Ensembles for Time Series Regressions
토론
이 논문과 연결된 포럼 글이 아직 없습니다.