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The topology of politics: voting connectivity in the US House of Representatives
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0001-6322-7542
Stanford University. (Department of Mathematics)
Ayasdi Inc..
Ayasdi Inc..
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2012 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Time-varying topological simplifications of the space of votes in the US House of Representatives (US HoR) display several interesting features unavailable with classical methods of machine learning. In this paper we demonstrate how a re- cently developed topological simplification method, MAPPER, can detect changes in collaboration structures within the US HoR over time.

Place, publisher, year, edition, pages
2012.
Keyword [en]
applied algebraic topology, political data analysis, parliament, house of representative, vote space, mapper, topological simplification
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-107212OAI: oai:DiVA.org:kth-107212DiVA: diva2:575331
Conference
NIPS 2012 Workshop on Algebraic Topology and Machine Learning
Funder
EU, FP7, Seventh Framework Programme, FP7-ICT-318493-STREP
Note

QC 20130523

Available from: 2012-12-10 Created: 2012-12-10 Last updated: 2013-05-23Bibliographically approved

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Vejdemo-Johansson, Mikael

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